{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "7b58db83",
   "metadata": {
    "heading_collapsed": true
   },
   "source": [
    "# 一、数据读取"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "8cbf3e54",
   "metadata": {
    "hidden": true
   },
   "outputs": [],
   "source": [
    "#导包\n",
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "\n",
    "#查找中文字体列表\n",
    "# v=[f.name for f in matplotlib.font_manager.fontManager.ttflist]\n",
    "# for i in v:\n",
    "#     if i[:3]=='Sim':\n",
    "#         print(i)\n",
    "#     else:\n",
    "#         continue\n",
    "plt.rcParams['font.family'] = ['sans-serif']\n",
    "plt.rcParams['font.sans-serif'] = 'SimHei'\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "26367574",
   "metadata": {
    "hidden": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>RowID</th>\n",
       "      <th>OrderID</th>\n",
       "      <th>OrderDate</th>\n",
       "      <th>ShipDate</th>\n",
       "      <th>ShipMode</th>\n",
       "      <th>CustomerID</th>\n",
       "      <th>CustomerName</th>\n",
       "      <th>Segment</th>\n",
       "      <th>City</th>\n",
       "      <th>State</th>\n",
       "      <th>...</th>\n",
       "      <th>ProductID</th>\n",
       "      <th>Category</th>\n",
       "      <th>Sub-Category</th>\n",
       "      <th>ProductName</th>\n",
       "      <th>Sales</th>\n",
       "      <th>Quantity</th>\n",
       "      <th>Discount</th>\n",
       "      <th>Profit</th>\n",
       "      <th>ShippingCost</th>\n",
       "      <th>OrderPriority</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>IN-2011-47883</td>\n",
       "      <td>2011/1/1</td>\n",
       "      <td>2011/1/8</td>\n",
       "      <td>Standard Class</td>\n",
       "      <td>JH-15985</td>\n",
       "      <td>Joseph Holt</td>\n",
       "      <td>Consumer</td>\n",
       "      <td>Wagga Wagga</td>\n",
       "      <td>New South Wales</td>\n",
       "      <td>...</td>\n",
       "      <td>OFF-SU-10000618</td>\n",
       "      <td>Office Supplies</td>\n",
       "      <td>Supplies</td>\n",
       "      <td>Acme Trimmer, High Speed</td>\n",
       "      <td>120.366</td>\n",
       "      <td>3</td>\n",
       "      <td>0.1</td>\n",
       "      <td>36.036</td>\n",
       "      <td>9.72</td>\n",
       "      <td>Medium</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>IN-2011-47883</td>\n",
       "      <td>2011/1/1</td>\n",
       "      <td>2011/1/8</td>\n",
       "      <td>Standard Class</td>\n",
       "      <td>JH-15985</td>\n",
       "      <td>Joseph Holt</td>\n",
       "      <td>Consumer</td>\n",
       "      <td>Wagga Wagga</td>\n",
       "      <td>New South Wales</td>\n",
       "      <td>...</td>\n",
       "      <td>OFF-PA-10001968</td>\n",
       "      <td>Office Supplies</td>\n",
       "      <td>Paper</td>\n",
       "      <td>Eaton Computer Printout Paper, 8.5 x 11</td>\n",
       "      <td>55.242</td>\n",
       "      <td>2</td>\n",
       "      <td>0.1</td>\n",
       "      <td>15.342</td>\n",
       "      <td>1.80</td>\n",
       "      <td>Medium</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>IN-2011-47883</td>\n",
       "      <td>2011/1/1</td>\n",
       "      <td>2011/1/8</td>\n",
       "      <td>Standard Class</td>\n",
       "      <td>JH-15985</td>\n",
       "      <td>Joseph Holt</td>\n",
       "      <td>Consumer</td>\n",
       "      <td>Wagga Wagga</td>\n",
       "      <td>New South Wales</td>\n",
       "      <td>...</td>\n",
       "      <td>FUR-FU-10003447</td>\n",
       "      <td>Furniture</td>\n",
       "      <td>Furnishings</td>\n",
       "      <td>Eldon Light Bulb, Duo Pack</td>\n",
       "      <td>113.670</td>\n",
       "      <td>5</td>\n",
       "      <td>0.1</td>\n",
       "      <td>37.770</td>\n",
       "      <td>4.70</td>\n",
       "      <td>Medium</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>IT-2011-3647632</td>\n",
       "      <td>2011/1/1</td>\n",
       "      <td>2011/1/5</td>\n",
       "      <td>Second Class</td>\n",
       "      <td>EM-14140</td>\n",
       "      <td>Eugene Moren</td>\n",
       "      <td>Home Office</td>\n",
       "      <td>Stockholm</td>\n",
       "      <td>Stockholm</td>\n",
       "      <td>...</td>\n",
       "      <td>OFF-PA-10001492</td>\n",
       "      <td>Office Supplies</td>\n",
       "      <td>Paper</td>\n",
       "      <td>Enermax Note Cards, Premium</td>\n",
       "      <td>44.865</td>\n",
       "      <td>3</td>\n",
       "      <td>0.5</td>\n",
       "      <td>-26.055</td>\n",
       "      <td>4.82</td>\n",
       "      <td>High</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>HU-2011-1220</td>\n",
       "      <td>2011/1/1</td>\n",
       "      <td>2011/1/5</td>\n",
       "      <td>Second Class</td>\n",
       "      <td>AT-735</td>\n",
       "      <td>Annie Thurman</td>\n",
       "      <td>Consumer</td>\n",
       "      <td>Budapest</td>\n",
       "      <td>Budapest</td>\n",
       "      <td>...</td>\n",
       "      <td>OFF-TEN-10001585</td>\n",
       "      <td>Office Supplies</td>\n",
       "      <td>Storage</td>\n",
       "      <td>Tenex Box, Single Width</td>\n",
       "      <td>66.120</td>\n",
       "      <td>4</td>\n",
       "      <td>0.0</td>\n",
       "      <td>29.640</td>\n",
       "      <td>8.17</td>\n",
       "      <td>High</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>51096</th>\n",
       "      <td>51094</td>\n",
       "      <td>IN-2014-75603</td>\n",
       "      <td>2014/12/31</td>\n",
       "      <td>2015/1/5</td>\n",
       "      <td>Second Class</td>\n",
       "      <td>BS-11365</td>\n",
       "      <td>Bill Shonely</td>\n",
       "      <td>Corporate</td>\n",
       "      <td>Vijayawada</td>\n",
       "      <td>Andhra Pradesh</td>\n",
       "      <td>...</td>\n",
       "      <td>OFF-FA-10000263</td>\n",
       "      <td>Office Supplies</td>\n",
       "      <td>Fasteners</td>\n",
       "      <td>Stockwell Thumb Tacks, Bulk Pack</td>\n",
       "      <td>39.420</td>\n",
       "      <td>3</td>\n",
       "      <td>0.0</td>\n",
       "      <td>17.280</td>\n",
       "      <td>2.97</td>\n",
       "      <td>Medium</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>51097</th>\n",
       "      <td>51095</td>\n",
       "      <td>TU-2014-5170</td>\n",
       "      <td>2014/12/31</td>\n",
       "      <td>2015/1/4</td>\n",
       "      <td>Second Class</td>\n",
       "      <td>VD-11670</td>\n",
       "      <td>Valerie Dominguez</td>\n",
       "      <td>Consumer</td>\n",
       "      <td>Konya</td>\n",
       "      <td>Konya</td>\n",
       "      <td>...</td>\n",
       "      <td>FUR-TEN-10000558</td>\n",
       "      <td>Furniture</td>\n",
       "      <td>Furnishings</td>\n",
       "      <td>Tenex Frame, Erganomic</td>\n",
       "      <td>173.760</td>\n",
       "      <td>4</td>\n",
       "      <td>0.6</td>\n",
       "      <td>-117.360</td>\n",
       "      <td>13.72</td>\n",
       "      <td>Medium</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>51098</th>\n",
       "      <td>51096</td>\n",
       "      <td>MO-2014-2560</td>\n",
       "      <td>2014/12/31</td>\n",
       "      <td>2015/1/5</td>\n",
       "      <td>Standard Class</td>\n",
       "      <td>LP-7095</td>\n",
       "      <td>Liz Preis</td>\n",
       "      <td>Consumer</td>\n",
       "      <td>Agadir</td>\n",
       "      <td>Souss-M</td>\n",
       "      <td>...</td>\n",
       "      <td>OFF-WIL-10001069</td>\n",
       "      <td>Office Supplies</td>\n",
       "      <td>Binders</td>\n",
       "      <td>Wilson Jones Hole Reinforcements, Clear</td>\n",
       "      <td>3.990</td>\n",
       "      <td>1</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.420</td>\n",
       "      <td>0.49</td>\n",
       "      <td>Medium</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>51099</th>\n",
       "      <td>51097</td>\n",
       "      <td>ES-2014-4785777</td>\n",
       "      <td>2014/12/31</td>\n",
       "      <td>2015/1/4</td>\n",
       "      <td>Standard Class</td>\n",
       "      <td>DP-13390</td>\n",
       "      <td>Dennis Pardue</td>\n",
       "      <td>Home Office</td>\n",
       "      <td>Hamburg</td>\n",
       "      <td>Hamburg</td>\n",
       "      <td>...</td>\n",
       "      <td>OFF-BI-10000620</td>\n",
       "      <td>Office Supplies</td>\n",
       "      <td>Binders</td>\n",
       "      <td>Wilson Jones Index Tab, Economy</td>\n",
       "      <td>32.250</td>\n",
       "      <td>5</td>\n",
       "      <td>0.0</td>\n",
       "      <td>8.250</td>\n",
       "      <td>2.21</td>\n",
       "      <td>Medium</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>51100</th>\n",
       "      <td>51098</td>\n",
       "      <td>CA-2014-143259</td>\n",
       "      <td>2014/12/31</td>\n",
       "      <td>2015/1/4</td>\n",
       "      <td>Standard Class</td>\n",
       "      <td>PO-18865</td>\n",
       "      <td>Patrick O'Donnell</td>\n",
       "      <td>Consumer</td>\n",
       "      <td>New York City</td>\n",
       "      <td>New York</td>\n",
       "      <td>...</td>\n",
       "      <td>OFF-BI-10003684</td>\n",
       "      <td>Office Supplies</td>\n",
       "      <td>Binders</td>\n",
       "      <td>Wilson Jones Legal Size Ring Binders</td>\n",
       "      <td>52.776</td>\n",
       "      <td>3</td>\n",
       "      <td>0.2</td>\n",
       "      <td>19.791</td>\n",
       "      <td>7.21</td>\n",
       "      <td>High</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>51101 rows × 24 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "       RowID          OrderID   OrderDate  ShipDate        ShipMode  \\\n",
       "0          1    IN-2011-47883    2011/1/1  2011/1/8  Standard Class   \n",
       "1          2    IN-2011-47883    2011/1/1  2011/1/8  Standard Class   \n",
       "2          3    IN-2011-47883    2011/1/1  2011/1/8  Standard Class   \n",
       "3          4  IT-2011-3647632    2011/1/1  2011/1/5    Second Class   \n",
       "4          5     HU-2011-1220    2011/1/1  2011/1/5    Second Class   \n",
       "...      ...              ...         ...       ...             ...   \n",
       "51096  51094    IN-2014-75603  2014/12/31  2015/1/5    Second Class   \n",
       "51097  51095     TU-2014-5170  2014/12/31  2015/1/4    Second Class   \n",
       "51098  51096     MO-2014-2560  2014/12/31  2015/1/5  Standard Class   \n",
       "51099  51097  ES-2014-4785777  2014/12/31  2015/1/4  Standard Class   \n",
       "51100  51098   CA-2014-143259  2014/12/31  2015/1/4  Standard Class   \n",
       "\n",
       "      CustomerID       CustomerName      Segment           City  \\\n",
       "0       JH-15985        Joseph Holt     Consumer    Wagga Wagga   \n",
       "1       JH-15985        Joseph Holt     Consumer    Wagga Wagga   \n",
       "2       JH-15985        Joseph Holt     Consumer    Wagga Wagga   \n",
       "3       EM-14140       Eugene Moren  Home Office      Stockholm   \n",
       "4         AT-735      Annie Thurman     Consumer       Budapest   \n",
       "...          ...                ...          ...            ...   \n",
       "51096   BS-11365       Bill Shonely    Corporate     Vijayawada   \n",
       "51097   VD-11670  Valerie Dominguez     Consumer          Konya   \n",
       "51098    LP-7095          Liz Preis     Consumer         Agadir   \n",
       "51099   DP-13390      Dennis Pardue  Home Office        Hamburg   \n",
       "51100   PO-18865  Patrick O'Donnell     Consumer  New York City   \n",
       "\n",
       "                 State  ...         ProductID         Category Sub-Category  \\\n",
       "0      New South Wales  ...   OFF-SU-10000618  Office Supplies     Supplies   \n",
       "1      New South Wales  ...   OFF-PA-10001968  Office Supplies        Paper   \n",
       "2      New South Wales  ...   FUR-FU-10003447        Furniture  Furnishings   \n",
       "3            Stockholm  ...   OFF-PA-10001492  Office Supplies        Paper   \n",
       "4             Budapest  ...  OFF-TEN-10001585  Office Supplies      Storage   \n",
       "...                ...  ...               ...              ...          ...   \n",
       "51096   Andhra Pradesh  ...   OFF-FA-10000263  Office Supplies    Fasteners   \n",
       "51097            Konya  ...  FUR-TEN-10000558        Furniture  Furnishings   \n",
       "51098          Souss-M  ...  OFF-WIL-10001069  Office Supplies      Binders   \n",
       "51099          Hamburg  ...   OFF-BI-10000620  Office Supplies      Binders   \n",
       "51100         New York  ...   OFF-BI-10003684  Office Supplies      Binders   \n",
       "\n",
       "                                   ProductName    Sales Quantity Discount  \\\n",
       "0                     Acme Trimmer, High Speed  120.366        3      0.1   \n",
       "1      Eaton Computer Printout Paper, 8.5 x 11   55.242        2      0.1   \n",
       "2                   Eldon Light Bulb, Duo Pack  113.670        5      0.1   \n",
       "3                  Enermax Note Cards, Premium   44.865        3      0.5   \n",
       "4                      Tenex Box, Single Width   66.120        4      0.0   \n",
       "...                                        ...      ...      ...      ...   \n",
       "51096         Stockwell Thumb Tacks, Bulk Pack   39.420        3      0.0   \n",
       "51097                   Tenex Frame, Erganomic  173.760        4      0.6   \n",
       "51098  Wilson Jones Hole Reinforcements, Clear    3.990        1      0.0   \n",
       "51099          Wilson Jones Index Tab, Economy   32.250        5      0.0   \n",
       "51100     Wilson Jones Legal Size Ring Binders   52.776        3      0.2   \n",
       "\n",
       "        Profit  ShippingCost  OrderPriority  \n",
       "0       36.036          9.72         Medium  \n",
       "1       15.342          1.80         Medium  \n",
       "2       37.770          4.70         Medium  \n",
       "3      -26.055          4.82           High  \n",
       "4       29.640          8.17           High  \n",
       "...        ...           ...            ...  \n",
       "51096   17.280          2.97         Medium  \n",
       "51097 -117.360         13.72         Medium  \n",
       "51098    0.420          0.49         Medium  \n",
       "51099    8.250          2.21         Medium  \n",
       "51100   19.791          7.21           High  \n",
       "\n",
       "[51101 rows x 24 columns]"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "<div class=\"burk\">\n",
    "data=pd.read_csv('./dataset.csv',encoding='ISO-8859-1')\n",
    "data</div><i class=\"fa fa-lightbulb-o \"></i>"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b4e52101",
   "metadata": {},
   "source": [
    "# 二、数据处理"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5397ed81",
   "metadata": {
    "heading_collapsed": true
   },
   "source": [
    "# 2.1提取业务数据"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "2859951a",
   "metadata": {
    "hidden": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>RowID</th>\n",
       "      <th>OrderID</th>\n",
       "      <th>OrderDate</th>\n",
       "      <th>ShipDate</th>\n",
       "      <th>ShipMode</th>\n",
       "      <th>CustomerID</th>\n",
       "      <th>CustomerName</th>\n",
       "      <th>Segment</th>\n",
       "      <th>City</th>\n",
       "      <th>State</th>\n",
       "      <th>...</th>\n",
       "      <th>Category</th>\n",
       "      <th>Sub-Category</th>\n",
       "      <th>ProductName</th>\n",
       "      <th>Sales</th>\n",
       "      <th>Quantity</th>\n",
       "      <th>Discount</th>\n",
       "      <th>Profit</th>\n",
       "      <th>ShippingCost</th>\n",
       "      <th>OrderPriority</th>\n",
       "      <th>interval</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>0 rows × 25 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "Empty DataFrame\n",
       "Columns: [RowID, OrderID, OrderDate, ShipDate, ShipMode, CustomerID, CustomerName, Segment, City, State, Country, PostalCode, Market, Region, ProductID, Category, Sub-Category, ProductName, Sales, Quantity, Discount, Profit, ShippingCost, OrderPriority, interval]\n",
       "Index: []\n",
       "\n",
       "[0 rows x 25 columns]"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 根据业务验证  发货日期早于下单日期  \n",
    "# 1. 日期格式 \n",
    "data['ShipDate']=pd.to_datetime(data['ShipDate'])\n",
    "data['OrderDate']=pd.to_datetime(data['OrderDate'])\n",
    "#2.日期间隔 做差\n",
    "data['interval']=(data.ShipDate-data.OrderDate).dt.total_seconds()\n",
    "data\n",
    "#异常数据\n",
    "data[data.interval<0]\n",
    "#删除异常数据\n",
    "data.drop(index=data[data.interval<0].index,inplace=True)\n",
    "data\n",
    "#售价为负\n",
    "data[data.Sales<0]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "eb85e586",
   "metadata": {
    "heading_collapsed": true
   },
   "source": [
    "# 2.2数据清洗"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "85a9bce7",
   "metadata": {
    "hidden": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Int64Index: 51097 entries, 0 to 51100\n",
      "Data columns (total 25 columns):\n",
      " #   Column         Non-Null Count  Dtype         \n",
      "---  ------         --------------  -----         \n",
      " 0   RowID          51097 non-null  int64         \n",
      " 1   OrderID        51097 non-null  object        \n",
      " 2   OrderDate      51097 non-null  datetime64[ns]\n",
      " 3   ShipDate       51097 non-null  datetime64[ns]\n",
      " 4   ShipMode       51086 non-null  object        \n",
      " 5   CustomerID     51097 non-null  object        \n",
      " 6   CustomerName   51097 non-null  object        \n",
      " 7   Segment        51097 non-null  object        \n",
      " 8   City           51097 non-null  object        \n",
      " 9   State          51097 non-null  object        \n",
      " 10  Country        51097 non-null  object        \n",
      " 11  PostalCode     9962 non-null   float64       \n",
      " 12  Market         51097 non-null  object        \n",
      " 13  Region         51097 non-null  object        \n",
      " 14  ProductID      51097 non-null  object        \n",
      " 15  Category       51097 non-null  object        \n",
      " 16  Sub-Category   51097 non-null  object        \n",
      " 17  ProductName    51097 non-null  object        \n",
      " 18  Sales          51097 non-null  float64       \n",
      " 19  Quantity       51097 non-null  int64         \n",
      " 20  Discount       51097 non-null  float64       \n",
      " 21  Profit         51097 non-null  float64       \n",
      " 22  ShippingCost   51097 non-null  float64       \n",
      " 23  OrderPriority  51097 non-null  object        \n",
      " 24  interval       51097 non-null  float64       \n",
      "dtypes: datetime64[ns](2), float64(6), int64(2), object(15)\n",
      "memory usage: 10.1+ MB\n"
     ]
    }
   ],
   "source": [
    "data.shape\n",
    "data.count()\n",
    "data.isna().sum()\n",
    "data.describe()\n",
    "data.info()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ad483e88",
   "metadata": {
    "hidden": true
   },
   "source": [
    "2.1Rowid"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "16478e32",
   "metadata": {
    "hidden": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>RowID</th>\n",
       "      <th>OrderID</th>\n",
       "      <th>OrderDate</th>\n",
       "      <th>ShipDate</th>\n",
       "      <th>ShipMode</th>\n",
       "      <th>CustomerID</th>\n",
       "      <th>CustomerName</th>\n",
       "      <th>Segment</th>\n",
       "      <th>City</th>\n",
       "      <th>State</th>\n",
       "      <th>...</th>\n",
       "      <th>Category</th>\n",
       "      <th>Sub-Category</th>\n",
       "      <th>ProductName</th>\n",
       "      <th>Sales</th>\n",
       "      <th>Quantity</th>\n",
       "      <th>Discount</th>\n",
       "      <th>Profit</th>\n",
       "      <th>ShippingCost</th>\n",
       "      <th>OrderPriority</th>\n",
       "      <th>interval</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>IN-2011-47883</td>\n",
       "      <td>2011-01-01</td>\n",
       "      <td>2011-01-08</td>\n",
       "      <td>Standard Class</td>\n",
       "      <td>JH-15985</td>\n",
       "      <td>Joseph Holt</td>\n",
       "      <td>Consumer</td>\n",
       "      <td>Wagga Wagga</td>\n",
       "      <td>New South Wales</td>\n",
       "      <td>...</td>\n",
       "      <td>Office Supplies</td>\n",
       "      <td>Supplies</td>\n",
       "      <td>Acme Trimmer, High Speed</td>\n",
       "      <td>120.366</td>\n",
       "      <td>3</td>\n",
       "      <td>0.1</td>\n",
       "      <td>36.036</td>\n",
       "      <td>9.72</td>\n",
       "      <td>Medium</td>\n",
       "      <td>604800.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>IN-2011-47883</td>\n",
       "      <td>2011-01-01</td>\n",
       "      <td>2011-01-08</td>\n",
       "      <td>Standard Class</td>\n",
       "      <td>JH-15985</td>\n",
       "      <td>Joseph Holt</td>\n",
       "      <td>Consumer</td>\n",
       "      <td>Wagga Wagga</td>\n",
       "      <td>New South Wales</td>\n",
       "      <td>...</td>\n",
       "      <td>Office Supplies</td>\n",
       "      <td>Paper</td>\n",
       "      <td>Eaton Computer Printout Paper, 8.5 x 11</td>\n",
       "      <td>55.242</td>\n",
       "      <td>2</td>\n",
       "      <td>0.1</td>\n",
       "      <td>15.342</td>\n",
       "      <td>1.80</td>\n",
       "      <td>Medium</td>\n",
       "      <td>604800.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>IN-2011-47883</td>\n",
       "      <td>2011-01-01</td>\n",
       "      <td>2011-01-08</td>\n",
       "      <td>Standard Class</td>\n",
       "      <td>JH-15985</td>\n",
       "      <td>Joseph Holt</td>\n",
       "      <td>Consumer</td>\n",
       "      <td>Wagga Wagga</td>\n",
       "      <td>New South Wales</td>\n",
       "      <td>...</td>\n",
       "      <td>Furniture</td>\n",
       "      <td>Furnishings</td>\n",
       "      <td>Eldon Light Bulb, Duo Pack</td>\n",
       "      <td>113.670</td>\n",
       "      <td>5</td>\n",
       "      <td>0.1</td>\n",
       "      <td>37.770</td>\n",
       "      <td>4.70</td>\n",
       "      <td>Medium</td>\n",
       "      <td>604800.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>IT-2011-3647632</td>\n",
       "      <td>2011-01-01</td>\n",
       "      <td>2011-01-05</td>\n",
       "      <td>Second Class</td>\n",
       "      <td>EM-14140</td>\n",
       "      <td>Eugene Moren</td>\n",
       "      <td>Home Office</td>\n",
       "      <td>Stockholm</td>\n",
       "      <td>Stockholm</td>\n",
       "      <td>...</td>\n",
       "      <td>Office Supplies</td>\n",
       "      <td>Paper</td>\n",
       "      <td>Enermax Note Cards, Premium</td>\n",
       "      <td>44.865</td>\n",
       "      <td>3</td>\n",
       "      <td>0.5</td>\n",
       "      <td>-26.055</td>\n",
       "      <td>4.82</td>\n",
       "      <td>High</td>\n",
       "      <td>345600.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>HU-2011-1220</td>\n",
       "      <td>2011-01-01</td>\n",
       "      <td>2011-01-05</td>\n",
       "      <td>Second Class</td>\n",
       "      <td>AT-735</td>\n",
       "      <td>Annie Thurman</td>\n",
       "      <td>Consumer</td>\n",
       "      <td>Budapest</td>\n",
       "      <td>Budapest</td>\n",
       "      <td>...</td>\n",
       "      <td>Office Supplies</td>\n",
       "      <td>Storage</td>\n",
       "      <td>Tenex Box, Single Width</td>\n",
       "      <td>66.120</td>\n",
       "      <td>4</td>\n",
       "      <td>0.0</td>\n",
       "      <td>29.640</td>\n",
       "      <td>8.17</td>\n",
       "      <td>High</td>\n",
       "      <td>345600.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>51096</th>\n",
       "      <td>51094</td>\n",
       "      <td>IN-2014-75603</td>\n",
       "      <td>2014-12-31</td>\n",
       "      <td>2015-01-05</td>\n",
       "      <td>Second Class</td>\n",
       "      <td>BS-11365</td>\n",
       "      <td>Bill Shonely</td>\n",
       "      <td>Corporate</td>\n",
       "      <td>Vijayawada</td>\n",
       "      <td>Andhra Pradesh</td>\n",
       "      <td>...</td>\n",
       "      <td>Office Supplies</td>\n",
       "      <td>Fasteners</td>\n",
       "      <td>Stockwell Thumb Tacks, Bulk Pack</td>\n",
       "      <td>39.420</td>\n",
       "      <td>3</td>\n",
       "      <td>0.0</td>\n",
       "      <td>17.280</td>\n",
       "      <td>2.97</td>\n",
       "      <td>Medium</td>\n",
       "      <td>432000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>51097</th>\n",
       "      <td>51095</td>\n",
       "      <td>TU-2014-5170</td>\n",
       "      <td>2014-12-31</td>\n",
       "      <td>2015-01-04</td>\n",
       "      <td>Second Class</td>\n",
       "      <td>VD-11670</td>\n",
       "      <td>Valerie Dominguez</td>\n",
       "      <td>Consumer</td>\n",
       "      <td>Konya</td>\n",
       "      <td>Konya</td>\n",
       "      <td>...</td>\n",
       "      <td>Furniture</td>\n",
       "      <td>Furnishings</td>\n",
       "      <td>Tenex Frame, Erganomic</td>\n",
       "      <td>173.760</td>\n",
       "      <td>4</td>\n",
       "      <td>0.6</td>\n",
       "      <td>-117.360</td>\n",
       "      <td>13.72</td>\n",
       "      <td>Medium</td>\n",
       "      <td>345600.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>51098</th>\n",
       "      <td>51096</td>\n",
       "      <td>MO-2014-2560</td>\n",
       "      <td>2014-12-31</td>\n",
       "      <td>2015-01-05</td>\n",
       "      <td>Standard Class</td>\n",
       "      <td>LP-7095</td>\n",
       "      <td>Liz Preis</td>\n",
       "      <td>Consumer</td>\n",
       "      <td>Agadir</td>\n",
       "      <td>Souss-M</td>\n",
       "      <td>...</td>\n",
       "      <td>Office Supplies</td>\n",
       "      <td>Binders</td>\n",
       "      <td>Wilson Jones Hole Reinforcements, Clear</td>\n",
       "      <td>3.990</td>\n",
       "      <td>1</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.420</td>\n",
       "      <td>0.49</td>\n",
       "      <td>Medium</td>\n",
       "      <td>432000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>51099</th>\n",
       "      <td>51097</td>\n",
       "      <td>ES-2014-4785777</td>\n",
       "      <td>2014-12-31</td>\n",
       "      <td>2015-01-04</td>\n",
       "      <td>Standard Class</td>\n",
       "      <td>DP-13390</td>\n",
       "      <td>Dennis Pardue</td>\n",
       "      <td>Home Office</td>\n",
       "      <td>Hamburg</td>\n",
       "      <td>Hamburg</td>\n",
       "      <td>...</td>\n",
       "      <td>Office Supplies</td>\n",
       "      <td>Binders</td>\n",
       "      <td>Wilson Jones Index Tab, Economy</td>\n",
       "      <td>32.250</td>\n",
       "      <td>5</td>\n",
       "      <td>0.0</td>\n",
       "      <td>8.250</td>\n",
       "      <td>2.21</td>\n",
       "      <td>Medium</td>\n",
       "      <td>345600.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>51100</th>\n",
       "      <td>51098</td>\n",
       "      <td>CA-2014-143259</td>\n",
       "      <td>2014-12-31</td>\n",
       "      <td>2015-01-04</td>\n",
       "      <td>Standard Class</td>\n",
       "      <td>PO-18865</td>\n",
       "      <td>Patrick O'Donnell</td>\n",
       "      <td>Consumer</td>\n",
       "      <td>New York City</td>\n",
       "      <td>New York</td>\n",
       "      <td>...</td>\n",
       "      <td>Office Supplies</td>\n",
       "      <td>Binders</td>\n",
       "      <td>Wilson Jones Legal Size Ring Binders</td>\n",
       "      <td>52.776</td>\n",
       "      <td>3</td>\n",
       "      <td>0.2</td>\n",
       "      <td>19.791</td>\n",
       "      <td>7.21</td>\n",
       "      <td>High</td>\n",
       "      <td>345600.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>51094 rows × 25 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "       RowID          OrderID  OrderDate   ShipDate        ShipMode  \\\n",
       "0          1    IN-2011-47883 2011-01-01 2011-01-08  Standard Class   \n",
       "1          2    IN-2011-47883 2011-01-01 2011-01-08  Standard Class   \n",
       "2          3    IN-2011-47883 2011-01-01 2011-01-08  Standard Class   \n",
       "3          4  IT-2011-3647632 2011-01-01 2011-01-05    Second Class   \n",
       "4          5     HU-2011-1220 2011-01-01 2011-01-05    Second Class   \n",
       "...      ...              ...        ...        ...             ...   \n",
       "51096  51094    IN-2014-75603 2014-12-31 2015-01-05    Second Class   \n",
       "51097  51095     TU-2014-5170 2014-12-31 2015-01-04    Second Class   \n",
       "51098  51096     MO-2014-2560 2014-12-31 2015-01-05  Standard Class   \n",
       "51099  51097  ES-2014-4785777 2014-12-31 2015-01-04  Standard Class   \n",
       "51100  51098   CA-2014-143259 2014-12-31 2015-01-04  Standard Class   \n",
       "\n",
       "      CustomerID       CustomerName      Segment           City  \\\n",
       "0       JH-15985        Joseph Holt     Consumer    Wagga Wagga   \n",
       "1       JH-15985        Joseph Holt     Consumer    Wagga Wagga   \n",
       "2       JH-15985        Joseph Holt     Consumer    Wagga Wagga   \n",
       "3       EM-14140       Eugene Moren  Home Office      Stockholm   \n",
       "4         AT-735      Annie Thurman     Consumer       Budapest   \n",
       "...          ...                ...          ...            ...   \n",
       "51096   BS-11365       Bill Shonely    Corporate     Vijayawada   \n",
       "51097   VD-11670  Valerie Dominguez     Consumer          Konya   \n",
       "51098    LP-7095          Liz Preis     Consumer         Agadir   \n",
       "51099   DP-13390      Dennis Pardue  Home Office        Hamburg   \n",
       "51100   PO-18865  Patrick O'Donnell     Consumer  New York City   \n",
       "\n",
       "                 State  ...         Category  Sub-Category  \\\n",
       "0      New South Wales  ...  Office Supplies      Supplies   \n",
       "1      New South Wales  ...  Office Supplies         Paper   \n",
       "2      New South Wales  ...        Furniture   Furnishings   \n",
       "3            Stockholm  ...  Office Supplies         Paper   \n",
       "4             Budapest  ...  Office Supplies       Storage   \n",
       "...                ...  ...              ...           ...   \n",
       "51096   Andhra Pradesh  ...  Office Supplies     Fasteners   \n",
       "51097            Konya  ...        Furniture   Furnishings   \n",
       "51098          Souss-M  ...  Office Supplies       Binders   \n",
       "51099          Hamburg  ...  Office Supplies       Binders   \n",
       "51100         New York  ...  Office Supplies       Binders   \n",
       "\n",
       "                                   ProductName    Sales Quantity Discount  \\\n",
       "0                     Acme Trimmer, High Speed  120.366        3      0.1   \n",
       "1      Eaton Computer Printout Paper, 8.5 x 11   55.242        2      0.1   \n",
       "2                   Eldon Light Bulb, Duo Pack  113.670        5      0.1   \n",
       "3                  Enermax Note Cards, Premium   44.865        3      0.5   \n",
       "4                      Tenex Box, Single Width   66.120        4      0.0   \n",
       "...                                        ...      ...      ...      ...   \n",
       "51096         Stockwell Thumb Tacks, Bulk Pack   39.420        3      0.0   \n",
       "51097                   Tenex Frame, Erganomic  173.760        4      0.6   \n",
       "51098  Wilson Jones Hole Reinforcements, Clear    3.990        1      0.0   \n",
       "51099          Wilson Jones Index Tab, Economy   32.250        5      0.0   \n",
       "51100     Wilson Jones Legal Size Ring Binders   52.776        3      0.2   \n",
       "\n",
       "        Profit ShippingCost  OrderPriority  interval  \n",
       "0       36.036         9.72         Medium  604800.0  \n",
       "1       15.342         1.80         Medium  604800.0  \n",
       "2       37.770         4.70         Medium  604800.0  \n",
       "3      -26.055         4.82           High  345600.0  \n",
       "4       29.640         8.17           High  345600.0  \n",
       "...        ...          ...            ...       ...  \n",
       "51096   17.280         2.97         Medium  432000.0  \n",
       "51097 -117.360        13.72         Medium  345600.0  \n",
       "51098    0.420         0.49         Medium  432000.0  \n",
       "51099    8.250         2.21         Medium  345600.0  \n",
       "51100   19.791         7.21           High  345600.0  \n",
       "\n",
       "[51094 rows x 25 columns]"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.RowID.unique().size\n",
    "#查找重复值\n",
    "data[data.RowID.duplicated()]\n",
    "#删除重复值\n",
    "data.drop(index=data[data.RowID.duplicated()].index,inplace=True)\n",
    "data"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3cd6a624",
   "metadata": {
    "hidden": true
   },
   "source": [
    "ShipMode发货模式"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "104aba74",
   "metadata": {
    "hidden": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Int64Index: 51094 entries, 0 to 51100\n",
      "Data columns (total 25 columns):\n",
      " #   Column         Non-Null Count  Dtype         \n",
      "---  ------         --------------  -----         \n",
      " 0   RowID          51094 non-null  int64         \n",
      " 1   OrderID        51094 non-null  object        \n",
      " 2   OrderDate      51094 non-null  datetime64[ns]\n",
      " 3   ShipDate       51094 non-null  datetime64[ns]\n",
      " 4   ShipMode       51094 non-null  object        \n",
      " 5   CustomerID     51094 non-null  object        \n",
      " 6   CustomerName   51094 non-null  object        \n",
      " 7   Segment        51094 non-null  object        \n",
      " 8   City           51094 non-null  object        \n",
      " 9   State          51094 non-null  object        \n",
      " 10  Country        51094 non-null  object        \n",
      " 11  PostalCode     9962 non-null   float64       \n",
      " 12  Market         51094 non-null  object        \n",
      " 13  Region         51094 non-null  object        \n",
      " 14  ProductID      51094 non-null  object        \n",
      " 15  Category       51094 non-null  object        \n",
      " 16  Sub-Category   51094 non-null  object        \n",
      " 17  ProductName    51094 non-null  object        \n",
      " 18  Sales          51094 non-null  float64       \n",
      " 19  Quantity       51094 non-null  int64         \n",
      " 20  Discount       51094 non-null  float64       \n",
      " 21  Profit         51094 non-null  float64       \n",
      " 22  ShippingCost   51094 non-null  float64       \n",
      " 23  OrderPriority  51094 non-null  object        \n",
      " 24  interval       51094 non-null  float64       \n",
      "dtypes: datetime64[ns](2), float64(6), int64(2), object(15)\n",
      "memory usage: 10.1+ MB\n"
     ]
    }
   ],
   "source": [
    "data[data.ShipMode.isnull()]#查找空数据\n",
    "#查找本列所在的众数，因为本列所列的是字符串格式，所以只能找众数\n",
    "data.ShipMode.mode()[0]\n",
    "#补全空数据\n",
    "data.ShipMode.fillna(value=data.ShipMode.mode()[0],inplace=True)\n",
    "data.info()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "31cadb68",
   "metadata": {
    "hidden": true
   },
   "source": [
    "2.2.3PostalCode "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "775973c8",
   "metadata": {
    "hidden": true
   },
   "outputs": [],
   "source": [
    "# data.drop(columns=['PostalCode'],inplace=True)\n",
    "# data\n",
    "#PostalCode 在本csv中并不重要，所以直接删除即可"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "id": "224fdd10",
   "metadata": {
    "hidden": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Int64Index: 51094 entries, 0 to 51100\n",
      "Data columns (total 24 columns):\n",
      " #   Column         Non-Null Count  Dtype         \n",
      "---  ------         --------------  -----         \n",
      " 0   RowID          51094 non-null  int64         \n",
      " 1   OrderID        51094 non-null  object        \n",
      " 2   OrderDate      51094 non-null  datetime64[ns]\n",
      " 3   ShipDate       51094 non-null  datetime64[ns]\n",
      " 4   ShipMode       51094 non-null  object        \n",
      " 5   CustomerID     51094 non-null  object        \n",
      " 6   CustomerName   51094 non-null  object        \n",
      " 7   Segment        51094 non-null  object        \n",
      " 8   City           51094 non-null  object        \n",
      " 9   State          51094 non-null  object        \n",
      " 10  Country        51094 non-null  object        \n",
      " 11  Market         51094 non-null  object        \n",
      " 12  Region         51094 non-null  object        \n",
      " 13  ProductID      51094 non-null  object        \n",
      " 14  Category       51094 non-null  object        \n",
      " 15  Sub-Category   51094 non-null  object        \n",
      " 16  ProductName    51094 non-null  object        \n",
      " 17  Sales          51094 non-null  float64       \n",
      " 18  Quantity       51094 non-null  int64         \n",
      " 19  Discount       51094 non-null  float64       \n",
      " 20  Profit         51094 non-null  float64       \n",
      " 21  ShippingCost   51094 non-null  float64       \n",
      " 22  OrderPriority  51094 non-null  object        \n",
      " 23  interval       51094 non-null  float64       \n",
      "dtypes: datetime64[ns](2), float64(5), int64(2), object(15)\n",
      "memory usage: 9.7+ MB\n"
     ]
    }
   ],
   "source": [
    "data.info()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "897d3d1e",
   "metadata": {
    "hidden": true
   },
   "source": [
    "2.2.4Discount 处理"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "bb6000b7",
   "metadata": {
    "hidden": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>RowID</th>\n",
       "      <th>OrderID</th>\n",
       "      <th>OrderDate</th>\n",
       "      <th>ShipDate</th>\n",
       "      <th>ShipMode</th>\n",
       "      <th>CustomerID</th>\n",
       "      <th>CustomerName</th>\n",
       "      <th>Segment</th>\n",
       "      <th>City</th>\n",
       "      <th>State</th>\n",
       "      <th>...</th>\n",
       "      <th>Category</th>\n",
       "      <th>Sub-Category</th>\n",
       "      <th>ProductName</th>\n",
       "      <th>Sales</th>\n",
       "      <th>Quantity</th>\n",
       "      <th>Discount</th>\n",
       "      <th>Profit</th>\n",
       "      <th>ShippingCost</th>\n",
       "      <th>OrderPriority</th>\n",
       "      <th>interval</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>IN-2011-47883</td>\n",
       "      <td>2011-01-01</td>\n",
       "      <td>2011-01-08</td>\n",
       "      <td>Standard Class</td>\n",
       "      <td>JH-15985</td>\n",
       "      <td>Joseph Holt</td>\n",
       "      <td>Consumer</td>\n",
       "      <td>Wagga Wagga</td>\n",
       "      <td>New South Wales</td>\n",
       "      <td>...</td>\n",
       "      <td>Office Supplies</td>\n",
       "      <td>Supplies</td>\n",
       "      <td>Acme Trimmer, High Speed</td>\n",
       "      <td>120.366</td>\n",
       "      <td>3</td>\n",
       "      <td>0.1</td>\n",
       "      <td>36.036</td>\n",
       "      <td>9.72</td>\n",
       "      <td>Medium</td>\n",
       "      <td>604800.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>IN-2011-47883</td>\n",
       "      <td>2011-01-01</td>\n",
       "      <td>2011-01-08</td>\n",
       "      <td>Standard Class</td>\n",
       "      <td>JH-15985</td>\n",
       "      <td>Joseph Holt</td>\n",
       "      <td>Consumer</td>\n",
       "      <td>Wagga Wagga</td>\n",
       "      <td>New South Wales</td>\n",
       "      <td>...</td>\n",
       "      <td>Office Supplies</td>\n",
       "      <td>Paper</td>\n",
       "      <td>Eaton Computer Printout Paper, 8.5 x 11</td>\n",
       "      <td>55.242</td>\n",
       "      <td>2</td>\n",
       "      <td>0.1</td>\n",
       "      <td>15.342</td>\n",
       "      <td>1.80</td>\n",
       "      <td>Medium</td>\n",
       "      <td>604800.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>IN-2011-47883</td>\n",
       "      <td>2011-01-01</td>\n",
       "      <td>2011-01-08</td>\n",
       "      <td>Standard Class</td>\n",
       "      <td>JH-15985</td>\n",
       "      <td>Joseph Holt</td>\n",
       "      <td>Consumer</td>\n",
       "      <td>Wagga Wagga</td>\n",
       "      <td>New South Wales</td>\n",
       "      <td>...</td>\n",
       "      <td>Furniture</td>\n",
       "      <td>Furnishings</td>\n",
       "      <td>Eldon Light Bulb, Duo Pack</td>\n",
       "      <td>113.670</td>\n",
       "      <td>5</td>\n",
       "      <td>0.1</td>\n",
       "      <td>37.770</td>\n",
       "      <td>4.70</td>\n",
       "      <td>Medium</td>\n",
       "      <td>604800.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>IT-2011-3647632</td>\n",
       "      <td>2011-01-01</td>\n",
       "      <td>2011-01-05</td>\n",
       "      <td>Second Class</td>\n",
       "      <td>EM-14140</td>\n",
       "      <td>Eugene Moren</td>\n",
       "      <td>Home Office</td>\n",
       "      <td>Stockholm</td>\n",
       "      <td>Stockholm</td>\n",
       "      <td>...</td>\n",
       "      <td>Office Supplies</td>\n",
       "      <td>Paper</td>\n",
       "      <td>Enermax Note Cards, Premium</td>\n",
       "      <td>44.865</td>\n",
       "      <td>3</td>\n",
       "      <td>0.5</td>\n",
       "      <td>-26.055</td>\n",
       "      <td>4.82</td>\n",
       "      <td>High</td>\n",
       "      <td>345600.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>HU-2011-1220</td>\n",
       "      <td>2011-01-01</td>\n",
       "      <td>2011-01-05</td>\n",
       "      <td>Second Class</td>\n",
       "      <td>AT-735</td>\n",
       "      <td>Annie Thurman</td>\n",
       "      <td>Consumer</td>\n",
       "      <td>Budapest</td>\n",
       "      <td>Budapest</td>\n",
       "      <td>...</td>\n",
       "      <td>Office Supplies</td>\n",
       "      <td>Storage</td>\n",
       "      <td>Tenex Box, Single Width</td>\n",
       "      <td>66.120</td>\n",
       "      <td>4</td>\n",
       "      <td>0.0</td>\n",
       "      <td>29.640</td>\n",
       "      <td>8.17</td>\n",
       "      <td>High</td>\n",
       "      <td>345600.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>51096</th>\n",
       "      <td>51094</td>\n",
       "      <td>IN-2014-75603</td>\n",
       "      <td>2014-12-31</td>\n",
       "      <td>2015-01-05</td>\n",
       "      <td>Second Class</td>\n",
       "      <td>BS-11365</td>\n",
       "      <td>Bill Shonely</td>\n",
       "      <td>Corporate</td>\n",
       "      <td>Vijayawada</td>\n",
       "      <td>Andhra Pradesh</td>\n",
       "      <td>...</td>\n",
       "      <td>Office Supplies</td>\n",
       "      <td>Fasteners</td>\n",
       "      <td>Stockwell Thumb Tacks, Bulk Pack</td>\n",
       "      <td>39.420</td>\n",
       "      <td>3</td>\n",
       "      <td>0.0</td>\n",
       "      <td>17.280</td>\n",
       "      <td>2.97</td>\n",
       "      <td>Medium</td>\n",
       "      <td>432000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>51097</th>\n",
       "      <td>51095</td>\n",
       "      <td>TU-2014-5170</td>\n",
       "      <td>2014-12-31</td>\n",
       "      <td>2015-01-04</td>\n",
       "      <td>Second Class</td>\n",
       "      <td>VD-11670</td>\n",
       "      <td>Valerie Dominguez</td>\n",
       "      <td>Consumer</td>\n",
       "      <td>Konya</td>\n",
       "      <td>Konya</td>\n",
       "      <td>...</td>\n",
       "      <td>Furniture</td>\n",
       "      <td>Furnishings</td>\n",
       "      <td>Tenex Frame, Erganomic</td>\n",
       "      <td>173.760</td>\n",
       "      <td>4</td>\n",
       "      <td>0.6</td>\n",
       "      <td>-117.360</td>\n",
       "      <td>13.72</td>\n",
       "      <td>Medium</td>\n",
       "      <td>345600.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>51098</th>\n",
       "      <td>51096</td>\n",
       "      <td>MO-2014-2560</td>\n",
       "      <td>2014-12-31</td>\n",
       "      <td>2015-01-05</td>\n",
       "      <td>Standard Class</td>\n",
       "      <td>LP-7095</td>\n",
       "      <td>Liz Preis</td>\n",
       "      <td>Consumer</td>\n",
       "      <td>Agadir</td>\n",
       "      <td>Souss-M</td>\n",
       "      <td>...</td>\n",
       "      <td>Office Supplies</td>\n",
       "      <td>Binders</td>\n",
       "      <td>Wilson Jones Hole Reinforcements, Clear</td>\n",
       "      <td>3.990</td>\n",
       "      <td>1</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.420</td>\n",
       "      <td>0.49</td>\n",
       "      <td>Medium</td>\n",
       "      <td>432000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>51099</th>\n",
       "      <td>51097</td>\n",
       "      <td>ES-2014-4785777</td>\n",
       "      <td>2014-12-31</td>\n",
       "      <td>2015-01-04</td>\n",
       "      <td>Standard Class</td>\n",
       "      <td>DP-13390</td>\n",
       "      <td>Dennis Pardue</td>\n",
       "      <td>Home Office</td>\n",
       "      <td>Hamburg</td>\n",
       "      <td>Hamburg</td>\n",
       "      <td>...</td>\n",
       "      <td>Office Supplies</td>\n",
       "      <td>Binders</td>\n",
       "      <td>Wilson Jones Index Tab, Economy</td>\n",
       "      <td>32.250</td>\n",
       "      <td>5</td>\n",
       "      <td>0.0</td>\n",
       "      <td>8.250</td>\n",
       "      <td>2.21</td>\n",
       "      <td>Medium</td>\n",
       "      <td>345600.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>51100</th>\n",
       "      <td>51098</td>\n",
       "      <td>CA-2014-143259</td>\n",
       "      <td>2014-12-31</td>\n",
       "      <td>2015-01-04</td>\n",
       "      <td>Standard Class</td>\n",
       "      <td>PO-18865</td>\n",
       "      <td>Patrick O'Donnell</td>\n",
       "      <td>Consumer</td>\n",
       "      <td>New York City</td>\n",
       "      <td>New York</td>\n",
       "      <td>...</td>\n",
       "      <td>Office Supplies</td>\n",
       "      <td>Binders</td>\n",
       "      <td>Wilson Jones Legal Size Ring Binders</td>\n",
       "      <td>52.776</td>\n",
       "      <td>3</td>\n",
       "      <td>0.2</td>\n",
       "      <td>19.791</td>\n",
       "      <td>7.21</td>\n",
       "      <td>High</td>\n",
       "      <td>345600.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>51094 rows × 25 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "       RowID          OrderID  OrderDate   ShipDate        ShipMode  \\\n",
       "0          1    IN-2011-47883 2011-01-01 2011-01-08  Standard Class   \n",
       "1          2    IN-2011-47883 2011-01-01 2011-01-08  Standard Class   \n",
       "2          3    IN-2011-47883 2011-01-01 2011-01-08  Standard Class   \n",
       "3          4  IT-2011-3647632 2011-01-01 2011-01-05    Second Class   \n",
       "4          5     HU-2011-1220 2011-01-01 2011-01-05    Second Class   \n",
       "...      ...              ...        ...        ...             ...   \n",
       "51096  51094    IN-2014-75603 2014-12-31 2015-01-05    Second Class   \n",
       "51097  51095     TU-2014-5170 2014-12-31 2015-01-04    Second Class   \n",
       "51098  51096     MO-2014-2560 2014-12-31 2015-01-05  Standard Class   \n",
       "51099  51097  ES-2014-4785777 2014-12-31 2015-01-04  Standard Class   \n",
       "51100  51098   CA-2014-143259 2014-12-31 2015-01-04  Standard Class   \n",
       "\n",
       "      CustomerID       CustomerName      Segment           City  \\\n",
       "0       JH-15985        Joseph Holt     Consumer    Wagga Wagga   \n",
       "1       JH-15985        Joseph Holt     Consumer    Wagga Wagga   \n",
       "2       JH-15985        Joseph Holt     Consumer    Wagga Wagga   \n",
       "3       EM-14140       Eugene Moren  Home Office      Stockholm   \n",
       "4         AT-735      Annie Thurman     Consumer       Budapest   \n",
       "...          ...                ...          ...            ...   \n",
       "51096   BS-11365       Bill Shonely    Corporate     Vijayawada   \n",
       "51097   VD-11670  Valerie Dominguez     Consumer          Konya   \n",
       "51098    LP-7095          Liz Preis     Consumer         Agadir   \n",
       "51099   DP-13390      Dennis Pardue  Home Office        Hamburg   \n",
       "51100   PO-18865  Patrick O'Donnell     Consumer  New York City   \n",
       "\n",
       "                 State  ...         Category  Sub-Category  \\\n",
       "0      New South Wales  ...  Office Supplies      Supplies   \n",
       "1      New South Wales  ...  Office Supplies         Paper   \n",
       "2      New South Wales  ...        Furniture   Furnishings   \n",
       "3            Stockholm  ...  Office Supplies         Paper   \n",
       "4             Budapest  ...  Office Supplies       Storage   \n",
       "...                ...  ...              ...           ...   \n",
       "51096   Andhra Pradesh  ...  Office Supplies     Fasteners   \n",
       "51097            Konya  ...        Furniture   Furnishings   \n",
       "51098          Souss-M  ...  Office Supplies       Binders   \n",
       "51099          Hamburg  ...  Office Supplies       Binders   \n",
       "51100         New York  ...  Office Supplies       Binders   \n",
       "\n",
       "                                   ProductName    Sales Quantity Discount  \\\n",
       "0                     Acme Trimmer, High Speed  120.366        3      0.1   \n",
       "1      Eaton Computer Printout Paper, 8.5 x 11   55.242        2      0.1   \n",
       "2                   Eldon Light Bulb, Duo Pack  113.670        5      0.1   \n",
       "3                  Enermax Note Cards, Premium   44.865        3      0.5   \n",
       "4                      Tenex Box, Single Width   66.120        4      0.0   \n",
       "...                                        ...      ...      ...      ...   \n",
       "51096         Stockwell Thumb Tacks, Bulk Pack   39.420        3      0.0   \n",
       "51097                   Tenex Frame, Erganomic  173.760        4      0.6   \n",
       "51098  Wilson Jones Hole Reinforcements, Clear    3.990        1      0.0   \n",
       "51099          Wilson Jones Index Tab, Economy   32.250        5      0.0   \n",
       "51100     Wilson Jones Legal Size Ring Binders   52.776        3      0.2   \n",
       "\n",
       "        Profit ShippingCost  OrderPriority  interval  \n",
       "0       36.036         9.72         Medium  604800.0  \n",
       "1       15.342         1.80         Medium  604800.0  \n",
       "2       37.770         4.70         Medium  604800.0  \n",
       "3      -26.055         4.82           High  345600.0  \n",
       "4       29.640         8.17           High  345600.0  \n",
       "...        ...          ...            ...       ...  \n",
       "51096   17.280         2.97         Medium  432000.0  \n",
       "51097 -117.360        13.72         Medium  345600.0  \n",
       "51098    0.420         0.49         Medium  432000.0  \n",
       "51099    8.250         2.21         Medium  345600.0  \n",
       "51100   19.791         7.21           High  345600.0  \n",
       "\n",
       "[51094 rows x 25 columns]"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#折扣 1-Discount\n",
    "data[data.Discount>1]\n",
    "data[data.Discount<0]\n",
    "#将异常值转为空值\n",
    "data['Discount']=data['Discount'].mask(data['Discount']>1,None)\n",
    "#求均值\n",
    "discount_mean=round(data.Discount.mean(),2)\n",
    "discount_mean\n",
    "#弥补 将空值填充为均值\n",
    "data['Discount'].fillna(value=discount_mean,inplace=True)\n",
    "data"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "bae6c16b",
   "metadata": {
    "heading_collapsed": true
   },
   "source": [
    "# 2.3数据规整"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "928c02f6",
   "metadata": {
    "hidden": true
   },
   "outputs": [],
   "source": [
    "#数据规整是根据经验和业务的需求将数据进行预处理\n",
    "#添加年份\n",
    "data['Order_year']=data.OrderDate.dt.year\n",
    "#添加月份\n",
    "data['Order_month']=data.OrderDate.dt.month\n",
    "# 添加季度\n",
    "data['Quter']=data.OrderDate.dt.to_period('Q')\n",
    "# data"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9977b470",
   "metadata": {},
   "source": [
    "# 三、数据分析"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "63f61b19",
   "metadata": {
    "heading_collapsed": true
   },
   "source": [
    "# 3.1每年销售额增长情况"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "59c64129",
   "metadata": {
    "hidden": true
   },
   "outputs": [
    {
     "ename": "NameError",
     "evalue": "name 'my_font' is not defined",
     "output_type": "error",
     "traceback": [
      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[1;31mNameError\u001b[0m                                 Traceback (most recent call last)",
      "\u001b[1;32m~\\AppData\\Local\\Temp/ipykernel_4628/1689394031.py\u001b[0m in \u001b[0;36m<module>\u001b[1;34m\u001b[0m\n\u001b[0;32m     34\u001b[0m \u001b[0max1\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mfig\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0madd_subplot\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;36m1\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;36m1\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;36m1\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m     35\u001b[0m \u001b[0max2\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0max1\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mtwinx\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m---> 36\u001b[1;33m \u001b[0max1\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mset_xlabel\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;34m'年份'\u001b[0m\u001b[1;33m,\u001b[0m\u001b[0mfontproperties\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mmy_font\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m     37\u001b[0m \u001b[0max1\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mset_ylabel\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;34m'销售额'\u001b[0m\u001b[1;33m,\u001b[0m\u001b[0mfontproperties\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mmy_font\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m     38\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;31mNameError\u001b[0m: name 'my_font' is not defined"
     ]
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAABRkAAAIGCAYAAADQoYhGAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjMuNCwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy8QVMy6AAAACXBIWXMAAAxOAAAMTgF/d4wjAAAacElEQVR4nO3dUYin913v8c93Z90mXUJBjBc9OdKDZFG0oJ4Ta4Oka4qkOQZURHqhSC5ErYKFvbGiINUELxqWBLzJoXBWcK+EI6dITjlqI2nJSkpKiiBFRWTZ4ilqlRAaKmf268X8t8wZdub/zP87/2ky5/WCZfnP/OZ5vnPxm5l97/M8U90dAAAAAIBNnftmDwAAAAAAvL2JjAAAAADAiMgIAAAAAIyIjAAAAADAiMgIAAAAAIyIjAAAAADAiMgIAAAAAIyIjAAAAADAyOLIWFXfUlUvVNXlNet+uapeq6rPVNWD0wEBAAAAgLlt9r3zCwe4kOR/Jnlgzbr3JvmVJP9ltfa5JP91yTkAAAAAgO3Ydt9bFBlXfj7J02vWfDDJH3X3m0n+pqreXVU73b17YNgrSa7se9N/OHfOndsAAAAAsInbt28nyZf3velqd189sOzE+t5BiyJjd/9bki9X1bql9yW5ue/115Lcn+T/HDje1STf+CR3dnZ6d/fIOQEAAACAQ1TVbncfepXiSfe9g0768sHXk1zc9/p8krWTAwAAAABvCRv1vZOOjDeSPJokVfWuJO9J8o8nfA4AAAAAYDs26nsbR8aq+lhVfWj/27r7lSTvqKpPJvlUkv/e3f9303MAAAAAANtxkn2vuvukh9tJ8kSSr3X3nyz5GM9kBAAAAIDNrZ7JeJxf8nzUsY7d9048Mm5CZAQAAACAzZ1kZNzEST+TEQAAAAD4/4zICAAAAACMiIwAAAAAwIjICAAAAACMiIwAAAAAwIjICAAAAACMiIwAAAAAwIjICAAAAACMiIwAAAAAwIjICAAAAACMiIwAAAAAwIjICAAAAACMiIwAAAAAwIjICAAAAACMiIwAAAAAwIjICAAAAACMiIwAAAAAwIjICAAAAACMiIwAAAAAwIjICAAAAACMiIwAAAAAwIjICAAAAACMiIwAAAAAwIjICAAAAACMiIwAAAAAwIjICAAAAACMiIwAAAAAwIjICAAAAACMiIwAAAAAwIjICAAAAACMiIwAAAAAwIjICAAAAACMiIwAAAAAwIjICAAAAACMiIwAAAAAwIjICAAAAACMiIwAAAAAwIjICAAAAACMiIwAAAAAwIjICAAAAACMiIwAAAAAwIjICAAAAACMiIwAAAAAwIjICAAAAACMiIwAAAAAwIjICAAAAACMiIwAAAAAwIjICAAAAACMiIwAAAAAwIjICAAAAACMiIwAAAAAwIjICAAAAACMiIwAAAAAwIjICAAAAACMiIwAAAAAwIjICAAAAACMiIwAAAAAwIjICAAAAACMiIwAAAAAwIjICAAAAACMiIwAAAAAwIjICAAAAACMiIwAAAAAwIjICAAAAACMiIwAAAAAwIjICAAAAACMiIwAAAAAwIjICAAAAACMiIwAAAAAwIjICAAAAACMiIwAAAAAwIjICAAAAACMiIwAAAAAwIjICAAAAACMiIwAAAAAwIjICAAAAACMiIwAAAAAwIjICAAAAACMiIwAAAAAwIjICAAAAACMiIwAAAAAwIjICAAAAACMiIwAAAAAwIjICAAAAACMiIwAAAAAwIjICAAAAACMiIwAAAAAwMiiyFhVT1fVq1X1QlXdf8S6T1TVS1X1SlX91MmNCQAAAABMbLPxrY2MVfV4koeTPJTkmSRPHbLue5N8T3c/kuSDSZ5dMgAAAAAAsF3bbnxLrmR8LMn17r6d5MXVMHfz1SQPrCroDyb56yUDAAAAAABbt9XGd37BmvuS3EyS7u6qunjIuq8keSXJR5L8pySfPOyAVXUlyZV9r5fMCgAAAADc3bmqurXv9dXuvrrv9Yk3vv2WRMbXk+w/6YVD1v1ckr/s7ueSpKo+V1Wf6e6vHFy4+gS/8Unu7Oz0kmEBAAAAgLu63d0PHPH+E298+y25XfpGkkdXB72U5I1D1l1M8n1Vda6q3pPkUpLdBccHAAAAALZrq42vuo++iLCq7knycpKXklxO8nySN5Oku6/tW/euJH+Q5AOr9z/T3Z9YN0CydyXj7q4eCQAAAACbqKrd7j70ruVtN761kXF18HuTPJHkVnffWPsBxyQyAgAAAMDm1kXG1ZqtNb5FkXHbREYAAAAA2NySyLhNS57JCAAAAABwKJERAAAAABgRGQEAAACAEZERAAAAABgRGQEAAACAEZERAAAAABgRGQEAAACAEZERAAAAABgRGQEAAACAEZERAAAAABgRGQEAAACAEZERAAAAABgRGQEAAACAEZERAAAAABgRGQEAAACAEZERAAAAABgRGQEAAACAEZERAAAAABgRGQEAAACAEZERAAAAABgRGQEAAACAEZERAAAAABgRGQEAAACAEZERAAAAABgRGQEAAACAEZERAAAAABgRGQEAAACAEZERAAAAABgRGQEAAACAEZERAAAAABgRGQEAAACAEZERAAAAABgRGQEAAACAEZERAAAAABgRGQEAAACAEZERAAAAABgRGQEAAACAEZERAAAAABgRGQEAAACAEZERAAAAABgRGQEAAACAEZERAAAAABgRGQEAAACAEZERAAAAABgRGQEAAACAEZERAAAAABgRGQEAAACAEZERAAAAABgRGQEAAACAEZERAAAAABgRGQEAAACAEZERAAAAABgRGQEAAACAEZERAAAAABgRGQEAAACAEZERAAAAABgRGQEAAACAEZERAAAAABgRGQEAAACAEZERAAAAABgRGQEAAACAEZERAAAAABgRGQEAAACAEZERAAAAABgRGQEAAACAEZERAAAAABgRGQEAAACAEZERAAAAABgRGQEAAACAEZERAAAAABgRGQEAAACAEZERAAAAABgRGQEAAACAEZERAAAAABgRGQEAAACAEZERAAAAABgRGQEAAACAEZERAAAAABgRGQEAAACAEZERAAAAABgRGQEAAACAEZERAAAAABgRGQEAAACAEZERAAAAABgRGQEAAACAEZERAAAAABgRGQEAAACAEZERAAAAABhZFBmr6umqerWqXqiq+9es/e6q+nxVveNkRgQAAAAAprbZ+NZGxqp6PMnDSR5K8kySp45YeyHJ7yf5pe7++pIBAAAAAIDt2nbjW3Il42NJrnf37SQvroY5zO+s/v6RqvquIwa9UlW37vzp7iWzAgAAAAB3d25/b6uqKwfef+KNb7/zC9bcl+RmknR3V9XFuy2qqu9M8uRq4NeT/GFV/Ux3f+ng2u6+muTqndc7OzsqIwAAAABs7nZ3P3DE+0+88e235ErG15PsP+mFQ9Z9f5JPd/dr3f13Sf4sySMLjg8AAAAAbNdWG9+SyHgjyaNJUlWXkrxxyLq/SnKpqnaq6nyS9yf52wXHBwAAAAC2a6uNr9Y9D7Gq7knycpKXklxO8nySN5Oku68dWPvrSX4ie5df/mmSj/aCBy7u7Oz07u7uumUAAAAAwF1U1W53H/poxG03vrWRcXXge5M8keRWd99Y+wHHJDICAAAAwObWRcbVmq01vkWRcdtERgAAAADY3JLIuE1LnskIAAAAAHAokREAAAAAGBEZAQAAAIARkREAAAAAGBEZAQAAAIARkREAAAAAGBEZAQAAAIARkREAAAAAGBEZAQAAAIARkREAAAAAGBEZAQAAAIARkREAAAAAGBEZAQAAAIARkREAAAAAGBEZAQAAAIARkREAAAAAGBEZAQAAAIARkREAAAAAGBEZAQAAAIARkREAAAAAGBEZAQAAAIARkREAAAAAGBEZAQAAAIARkREAAAAAGBEZAQAAAIARkREAAAAAGBEZAQAAAIARkREAAAAAGBEZAQAAAIARkREAAAAAGBEZAQAAAIARkREAAAAAGBEZAQAAAIARkREAAAAAGBEZAQAAAIARkREAAAAAGBEZAQAAAIARkREAAAAAGBEZAQAAAIARkREAAAAAGBEZAQAAAIARkREAAAAAGBEZAQAAAIARkREAAAAAGBEZAQAAAIARkREAAAAAGBEZAQAAAIARkREAAAAAGBEZAQAAAIARkREAAAAAGBEZAQAAAIARkREAAAAAGBEZAQAAAIARkREAAAAAGBEZAQAAAIARkREAAAAAGBEZAQAAAIARkREAAAAAGBEZAQAAAIARkREAAAAAGBEZAQAAAIARkREAAAAAGBEZAQAAAIARkREAAAAAGBEZAQAAAIARkREAAAAAGBEZAQAAAIARkREAAAAAGBEZAQAAAIARkREAAAAAGBEZAQAAAIARkREAAAAAGBEZAQAAAIARkREAAAAAGBEZAQAAAIARkREAAAAAGBEZAQAAAIARkREAAAAAGBEZAQAAAIARkREAAAAAGBEZAQAAAIARkREAAAAAGBEZAQAAAIARkREAAAAAGBEZAQAAAIARkREAAAAAGBEZAQAAAICRRZGxqp6uqler6oWqun/B+o9U1bXxdAAAAADAidhm41sbGavq8SQPJ3koyTNJnlqz/sEkv73k5AAAAADA9m278S25kvGxJNe7+3aSF1fDHHby80k+uW5IAAAAAOBUbbXxLYmM9yW5mSTd3UkuHrH2N5J8KskXjzpgVV2pqlt3/uwdFgAAAADY0Ln9va2qrhx4/4k3vv3OL1jz+oGTXrjboqp6KMn7kvxYkg8cdcDuvprk6p3XOzs7KiMAAAAAbO52dz9wxPtPvPHtt+RKxhtJHl2d5FKSNw5Z99NJvi17l1s+m+RDVfXxpYMAAAAAAFuz1cZX625Vrqp7kryc5KUkl5M8n+TNJOnua4d8zOUkT3b3k+sGSPauZNzd3V2yFAAAAAA4oKp2u/vQu5a33fjWRsbVAe9N8kSSW919Y+0HHJPICAAAAACbWxcZV2u21vgWRcZtExkBAAAAYHNLIuM2LXkmIwAAAADAoURGAAAAAGBEZAQAAAAARkRGAAAAAGBEZAQAAAAARkRGAAAAAGBEZAQAAAAARkRGAAAAAGBEZAQAAAAARkRGAAAAAGBEZAQAAAAARkRGAAAAAGBEZAQAAAAARkRGAAAAAGBEZAQAAAAARkRGAAAAAGBEZAQAAAAARkRGAAAAAGBEZAQAAAAARkRGAAAAAGBEZAQAAAAARkRGAAAAAGBEZAQAAAAARkRGAAAAAGBEZAQAAAAARkRGAAAAAGBEZAQAAAAARkRGAAAAAGBEZAQAAAAARkRGAAAAAGBEZAQAAAAARkRGAAAAAGBEZAQAAAAARkRGAAAAAGBEZAQAAAAARkRGAAAAAGBEZAQAAAAARkRGAAAAAGBEZAQAAAAARkRGAAAAAGBEZAQAAAAARkRGAAAAAGBEZAQAAAAARkRGAAAAAGBEZAQAAAAARkRGAAAAAGBEZAQAAAAARkRGAAAAAGBEZAQAAAAARkRGAAAAAGBEZAQAAAAARkRGAAAAAGBEZAQAAAAARkRGAAAAAGBEZAQAAAAARkRGAAAAAGBEZAQAAAAARkRGAAAAAGBEZAQAAAAARkRGAAAAAGBEZAQAAAAARkRGAAAAAGBEZAQAAAAARkRGAAAAAGBEZAQAAAAARkRGAAAAAGBEZAQAAAAARkRGAAAAAGBEZAQAAAAARkRGAAAAAGBEZAQAAAAARkRGAAAAAGBEZAQAAAAARkRGAAAAAGBEZAQAAAAARkRGAAAAAGBEZAQAAAAARkRGAAAAAGBEZAQAAAAARkRGAAAAAGBEZAQAAAAARkRGAAAAAGBEZAQAAAAARkRGAAAAAGBEZAQAAAAARkRGAAAAAGBEZAQAAAAARkRGAAAAAGBkUWSsqqer6tWqeqGq7j9i3e9W1eeq6pWq+ujJjQkAAAAATGyz8a2NjFX1eJKHkzyU5JkkTx2y7geSvLO7fzjJo0k+XlU7S4YAAAAAALZn243v/IIZHktyvbtvV9WLSZ6726Lu/kKSL6xefmuSf+nu3QXHBwAAAAC2a6uNb8nt0vclubk6SSe5eNTiqqokv5fkN49Yc6Wqbt35s3dYAAAAAGBD5/b3tqq6cuD9J9749ltyJePrB056Yc3630pys7uvH7agu68muXrn9c7OjsoIAAAAAJu73d0PHPH+E298+y25kvFG9u6/TlVdSvLGYQur6leTvDeJX/oCAAAAAG8dW218te5W5aq6J8nLSV5KcjnJ80neTJLuvrZv3aUkX0ryapKvr9784e7+8rohdnZ2enfX4xsBAAAAYBNVtdvdh961vO3GtzYyrg5+b5Inktzq7htrP+CYREYAAAAA2Ny6yLhas7XGtygybpvICAAAAACbWxIZt2nJMxkBAAAAAA4lMgIAAAAAIyIjAAAAADAiMgIAAAAAIyIjAAAAADAiMgIAAAAAIyIjAAAAADAiMgIAAAAAIyIjAAAAADAiMgIAAAAAIyIjAAAAADAiMgIAAAAAIyIjAAAAADAiMgIAAAAAIyIjAAAAADAiMgIAAAAAIyIjAAAAADAiMgIAAAAAIyIjAAAAADAiMgIAAAAAIyIjAAAAADAiMgIAAAAAIyIjAAAAADAiMgIAAAAAIyIjAAAAADAiMgIAAAAAIyIjAAAAADAiMgIAAAAAIyIjAAAAADAiMgIAAAAAIyIjAAAAADAiMgIAAAAAIyIjAAAAADAiMgIAAAAAIyIjAAAAADAiMgIAAAAAIyIjAAAAADAiMgIAAAAAIyIjAAAAADAiMgIAAAAAIyIjAAAAADAiMgIAAAAAIyIjAAAAADAiMgIAAAAAIyIjAAAAADAiMgIAAAAAIyIjAAAAADAiMgIAAAAAIyIjAAAAADAiMgIAAAAAIyIjAAAAADAiMgIAAAAAIyIjAAAAADAiMgIAAAAAIyIjAAAAADAiMgIAAAAAIyIjAAAAADAiMgIAAAAAIyIjAAAAADAiMgIAAAAAIyIjAAAAADAiMgIAAAAAIyIjAAAAADAiMgIAAAAAIyIjAAAAADAiMgIAAAAAIyIjAAAAADAiMgIAAAAAIyIjAAAAADAiMgIAAAAAIyIjAAAAADAiMgIAAAAAIyIjAAAAADAiMgIAAAAAIyIjAAAAADAiMgIAAAAAIyIjAAAAADAiMgIAAAAAIyIjAAAAADAiMgIAAAAAIyIjAAAAADAiMgIAAAAAIyIjAAAAADAiMgIAAAAAIyIjAAAAADAiMgIAAAAAIyIjAAAAADAiMgIAAAAAI4siY1U9XVWvVtULVXX/Eet+sqq+WFWfraofOrkxAQAAAICJbTa+8wtO/niSh5M8lORykqeS/OJd1n17kmeT/Ockt5P8ryTvWzIEAAAAALA92258ayNjkseSXO/u21X1YpLnDln3cJLPdvc/rQb656r6ju6+eZdhryS5cuBtuwtmAd5+zmXvixJw9tjfcHbZ33B22d9wdu1U1a19r69299V9r0+88e23JDLel+RmknR3V9XFdetW/jXJuw+8LavjXE3yjU+yqm519wMLZgHeZuxvOLvsbzi77G84u+xvOLsW7O8Tb3z7LXkm4+tJ9p/0wsJ155PUguMDAAAAANu11ca3JDLeSPJoklTVpSRvHLLulSSP1J6d7N2r/fcLjg8AAAAAbNdWG9+S26U/leRjVfVs9h4K+VxVPZkk3X3tzqLu/oeq+nySP1wd9y+6+x8WHD/Zd+s0cObY33B22d9wdtnfcHbZ33B2rdvfW2181d1rJ6yqe5M8keRWd99Ys/ZHk7wzyR93t1/mAgAAAABvAdtsfIsiIwAAAADAYZY8kxEAAAAA4FAiIwAAAAAwcmqRsaqerqpXq+qFqrr/iHU/WVVfrKrPVtUPndZ8wOaOsb9/t6o+V1WvVNVHT3NGYDNL9/e+9R+pqmunMBowdJz9XVXfXVWfr6p3nNZ8wOaO8fP5J6rqpdXP5z91mjMCm6mqb1nt7ctr1v1yVb1WVZ+pqgdPY7ZTiYxV9XiSh5M8lOSZJE8dsu7bkzyb5INJfjzJc6cxH7C5Y+zvH0jyzu7+4SSPJvl4Ve2c2qDAsS3d3/vWP5jkt09hNGDoOPu7qi4k+f0kv9TdXz+dCYFNHePn8+9N8j3d/Uj2/g3+7GnNCGxm9T35U0n+45p1703yK0nen+QXc0p97bSuZHwsyfXuvp3kxex9wbubh5N8trv/qbu/muSfq+o7TmlGYDOL9nd3f6G771y9+K1J/sVvoIe3vKXfv1NV55N8MmtCJPCWsXh/J/md1d8/UlXftfXJgKml+/urSR5YXen4g0n++pTmA2Z+Psmra9Z8MMkfdfeb3f03Sd59Ghf5nFZkvC/JzSTpvV9nfXHdupV/TfLurU4GTC3d30mSqqokv5fkN7c/GjB0nP39G9n7X9UvnsJcwNyi/V1V35nkySS/kOR/JLkuNMJb3tLv319J8kqSjyT52ez9ZyHwFtbd/9bdX16w9GBf+1qStY8+mjq/7ROsvJ7/9wvbhYXrziepbQ0FnIil+/uO30pys7uvb28k4IQs2t9V9VCS9yX5sSQfOIW5gLml37+/P8mnu/u1JKmqP0vySJIvbXU6YGLp/v65JH/Z3c8lyerZ6Z/p7q9se0Bg674pfe20rmS8kb1nsKWqLiV545B1ryR5pPbsZO8fLH9/KhMCm1q6v1NVv5rkvUn80hd4e1i6v386ybdl75asZ5N8qKo+fhoDAhtbur//KsmlqtpZPRbh/Un+9nRGBDa0dH9fTPJ9VXWuqt6T5FISjzOCs2H/14F3JXlPkn/c9klr7+rpLZ+k6p4kLyd5KcnlJM8neTNJuvvagbX/LXvPazuf5Ovd/eGtDwhsbOn+Xv2A86XsPTvizkPjP7zwUm/gm+A437/3fczlJE9295OnMCKwoWP+fP7rSX4ie7de/WmSj/Zp/CMC2Mgxfj5/V5I/yN5dCG8meaa7P3HK4wIbqKprSa51959X1ceSvNbdnz6w5n9n75bpB5P8RXf/2tbnOq2fD6rq3iRPJLnV3TfWrP3RJO9M8sd+MQS89R1nfwNvL/Y3nF32N5xd9jewukP4iSRf6+4/OZVz+k9IAAAAAGDitJ7JCAAAAACcUSIjAAAAADAiMgIAAAAAIyIjAAAAADAiMgIAAAAAIyIjAAAAADDy7yDGF9mh9J8jAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 1600x640 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 销售增长率 = (本年销售额-去年销售额)/去年销售额 *100% \n",
    "#            = 本年销售额/去年销售额 -1  \n",
    "#销售额\n",
    "sales_year=data.groupby('Order_year')['Sales'].sum()\n",
    "sales_year\n",
    "#销售增长率\n",
    "sales_rate_12=sales_year[2012]/sales_year[2011]-1\n",
    "sales_rate_13=sales_year[2013]/sales_year[2012]-1\n",
    "sales_rate_14=sales_year[2014]/sales_year[2013]-1\n",
    "# print(sales_rate_12,sales_rate_13,sales_rate_14)\n",
    "#销售增长率百分比\n",
    "sales_rate_12_label='%.2f%%'%(sales_rate_12*100)\n",
    "sales_rate_13_label='%.2f%%'%(sales_rate_13*100)\n",
    "sales_rate_14_label='%.2f%%'%(sales_rate_14*100)\n",
    "# print(sales_rate_12_label,sales_rate_13_label,sales_rate_14_label)\n",
    "sales_rate=pd.DataFrame(\n",
    "{\n",
    "    'sales_all':sales_year,\n",
    "    'sales_rate':[0,sales_rate_12,sales_rate_13,sales_rate_14],\n",
    "    'sales_rate_label':['0.00%',sales_rate_12_label,sales_rate_13_label,sales_rate_14_label]\n",
    "    \n",
    "}\n",
    ")\n",
    "sales_rate\n",
    "#数据准备\n",
    "x=[str(val) for val in sales_rate.index.tolist()]\n",
    "y1=sales_rate['sales_all']\n",
    "y2=sales_rate['sales_rate']\n",
    "#绘图\n",
    "fig=plt.figure(figsize=(20,8),dpi=80)\n",
    "#设置风格\n",
    "# plt.style.use('ggplot')\n",
    "\n",
    "ax1=fig.add_subplot(1,1,1)\n",
    "ax2=ax1.twinx()\n",
    "ax1.set_xlabel('年份',fontproperties=my_font)\n",
    "ax1.set_ylabel('销售额',fontproperties=my_font)\n",
    "\n",
    "ax2.set_ylabel('销售增长率',fontproperties=my_font)\n",
    "ax1.bar(x,y1,color='b')\n",
    "ax2.plot(x,y2,marker='*',color='r')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2a6a7c2e",
   "metadata": {
    "heading_collapsed": true
   },
   "source": [
    "# 3.2各个地区分店的销售额"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "bc303b7d",
   "metadata": {
    "hidden": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:title={'center':'占比'}, ylabel='Sales'>"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sales_area=data.groupby('Market')['Sales'].sum()\n",
    "sales_area.plot(kind='pie',autopct='%.1f%%',title='占比')\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "11b7c9eb",
   "metadata": {
    "heading_collapsed": true
   },
   "source": [
    "# 各地区每年销售额"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "a5249a5a",
   "metadata": {
    "hidden": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:title={'center':'2011-2014年各地区销售额'}, xlabel='Market'>"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "salas_aera=data.groupby(['Market','Order_year'])['Sales'].sum()\n",
    "\n",
    "# 多层索引数据转成单层索引  有两层索引时 level=[0,1],三层索引时level=[0,1,2]\n",
    "salas_aera=salas_aera.reset_index(level=[0,1])\n",
    "salas_aera\n",
    "# 透视 \n",
    "# pivot_table(数据源,行,列,数值)\n",
    "sales_area=pd.pivot_table(\n",
    "    salas_aera,\n",
    "    index='Market',\n",
    "    columns='Order_year',\n",
    "    values='Sales'\n",
    ")\n",
    "sales_area\n",
    "sales_area.plot(kind='bar',title='2011-2014年各地区销售额')\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e76ccf20",
   "metadata": {
    "heading_collapsed": true
   },
   "source": [
    "# 不同地区不同类型产品销售情况"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "b7671e91",
   "metadata": {
    "hidden": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:title={'center':'2011-2014不同地区销售额对比'}, xlabel='Market'>"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1440x576 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "category_sales_aera=data.groupby(['Market','Category'])['Sales'].sum()\n",
    "category_sales_aera\n",
    "# print(type(category_sales_aera))\n",
    "category_sales_aera.index\n",
    "# 多层索引数据转成单层索引 \n",
    "category_sales_aera=category_sales_aera.reset_index(level=[0,1])\n",
    "# 透视 \n",
    "# pivot_table(数据源,行,列,数值)\n",
    "category_sales_aera=pd.pivot_table(\n",
    "    category_sales_aera,\n",
    "    index='Market',\n",
    "    columns='Category',\n",
    "    values='Sales'\n",
    ")\n",
    "category_sales_aera.plot(kind='bar',title='2011-2014不同地区销售额对比',figsize=(20,8))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5ea60fd0",
   "metadata": {
    "heading_collapsed": true
   },
   "source": [
    "# 销售旺淡季"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "48e11266",
   "metadata": {
    "hidden": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:title={'center':'2011-2014销售淡旺季对比图'}, xlabel='Order_month'>"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1440x576 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sales_month=data.groupby(['Order_year','Order_month'])['Sales'].sum()\n",
    "sales_month\n",
    "#将单层索引转化为多层索引\n",
    "sales_month=sales_month.reset_index(level=[0,1])\n",
    "#透视表\n",
    "sales_month=pd.pivot_table(\n",
    "    sales_month,\n",
    "    index='Order_month',\n",
    "    columns='Order_year',\n",
    "    values='Sales'\n",
    ")\n",
    "sales_month.plot(title='2011-2014销售淡旺季对比图',figsize=(20,8),fontsize=20)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "89dd473f",
   "metadata": {
    "heading_collapsed": true
   },
   "source": [
    "# 客户数量"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "8033515a",
   "metadata": {
    "hidden": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th>Order_year</th>\n",
       "      <th>2011</th>\n",
       "      <th>2012</th>\n",
       "      <th>2013</th>\n",
       "      <th>2014</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Order_month</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>197</td>\n",
       "      <td>25</td>\n",
       "      <td>5</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>139</td>\n",
       "      <td>14</td>\n",
       "      <td>6</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>173</td>\n",
       "      <td>18</td>\n",
       "      <td>8</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>143</td>\n",
       "      <td>16</td>\n",
       "      <td>5</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>114</td>\n",
       "      <td>11</td>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>151</td>\n",
       "      <td>28</td>\n",
       "      <td>6</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>64</td>\n",
       "      <td>9</td>\n",
       "      <td>4</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>106</td>\n",
       "      <td>28</td>\n",
       "      <td>7</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>85</td>\n",
       "      <td>22</td>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>49</td>\n",
       "      <td>6</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>47</td>\n",
       "      <td>24</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>41</td>\n",
       "      <td>9</td>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "Order_year   2011  2012  2013  2014\n",
       "Order_month                        \n",
       "1             197    25     5     3\n",
       "2             139    14     6     3\n",
       "3             173    18     8     0\n",
       "4             143    16     5     1\n",
       "5             114    11     4     0\n",
       "6             151    28     6     6\n",
       "7              64     9     4     2\n",
       "8             106    28     7     0\n",
       "9              85    22     4     0\n",
       "10             49     6     2     0\n",
       "11             47    24     1     0\n",
       "12             41     9     4     0"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data_customer=data.copy()\n",
    "data_customer\n",
    "#删除重复用户数据 \n",
    "#drop_duplicates 保留一次出现的数据 剩下的重复数据删除\n",
    "\n",
    "data_customer=data_customer.drop_duplicates(subset=['CustomerID'])\n",
    "data_customer\n",
    "# 3.计算每一年,每一月用户数量 \n",
    "new_customer=data_customer.groupby(['Order_year','Order_month']).size()\n",
    "new_customer\n",
    "#转换数据，将单层索引转换为多层索引\n",
    "new_customer=new_customer.reset_index(level=[0,1])\n",
    "new_customer\n",
    "#数据透视\n",
    "new_customer_year=pd.pivot_table(\n",
    "    new_customer,\n",
    "    index='Order_month',\n",
    "    columns='Order_year',\n",
    "    values=0,\n",
    "    fill_value=0\n",
    ")\n",
    "new_customer_year"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "32f20042",
   "metadata": {
    "heading_collapsed": true
   },
   "source": [
    "# copy"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "72083db2",
   "metadata": {
    "hidden": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[1, 2, 3, 4, 100]\n",
      "[1, 2, 3, 4, 100]\n"
     ]
    }
   ],
   "source": [
    "lista = [1,2,3,4]\n",
    "listb = lista  # lista = [1,2,3,4]\n",
    "listb.append(100)\n",
    "print(listb)\n",
    "print(lista)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 201,
   "id": "3d5f064d",
   "metadata": {
    "hidden": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[5, 6, 7, 8]\n",
      "[5, 6, 7, 8, 10000]\n"
     ]
    }
   ],
   "source": [
    "listc = [5,6,7,8] \n",
    "listd = listc.copy() \n",
    "listd.append(10000)\n",
    "print(listc)\n",
    "print(listd)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "84ec8b20",
   "metadata": {
    "hidden": true
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 202,
   "id": "b4da5659",
   "metadata": {
    "hidden": true
   },
   "outputs": [],
   "source": [
    "# 4年数据 \n",
    "# 美团  注册 新用户 \n",
    "# 美团  产生第一次交易之前 新用户 "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "833c36b7",
   "metadata": {
    "hidden": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>OrderDate</th>\n",
       "      <th>M</th>\n",
       "      <th>F</th>\n",
       "      <th>R</th>\n",
       "      <th>label</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CustomerID</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>AA-10315</th>\n",
       "      <td>2014-12-23</td>\n",
       "      <td>3889.2065</td>\n",
       "      <td>17</td>\n",
       "      <td>8</td>\n",
       "      <td>重要价值客户</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>AA-10375</th>\n",
       "      <td>2014-12-25</td>\n",
       "      <td>1904.5380</td>\n",
       "      <td>14</td>\n",
       "      <td>6</td>\n",
       "      <td>潜力客户</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>AA-10480</th>\n",
       "      <td>2014-08-28</td>\n",
       "      <td>7752.9070</td>\n",
       "      <td>10</td>\n",
       "      <td>125</td>\n",
       "      <td>重要挽留客户</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>AA-10645</th>\n",
       "      <td>2014-12-03</td>\n",
       "      <td>3539.8788</td>\n",
       "      <td>19</td>\n",
       "      <td>28</td>\n",
       "      <td>重要价值客户</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>AA-315</th>\n",
       "      <td>2014-12-29</td>\n",
       "      <td>787.3920</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>新客户</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>YS-21880</th>\n",
       "      <td>2014-12-22</td>\n",
       "      <td>7282.4740</td>\n",
       "      <td>19</td>\n",
       "      <td>9</td>\n",
       "      <td>重要价值客户</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ZC-11910</th>\n",
       "      <td>2014-06-14</td>\n",
       "      <td>7.1730</td>\n",
       "      <td>1</td>\n",
       "      <td>200</td>\n",
       "      <td>流失客户</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ZC-21910</th>\n",
       "      <td>2014-12-28</td>\n",
       "      <td>4922.8390</td>\n",
       "      <td>27</td>\n",
       "      <td>3</td>\n",
       "      <td>重要价值客户</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ZD-11925</th>\n",
       "      <td>2014-12-28</td>\n",
       "      <td>856.2600</td>\n",
       "      <td>8</td>\n",
       "      <td>3</td>\n",
       "      <td>新客户</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ZD-21925</th>\n",
       "      <td>2014-12-30</td>\n",
       "      <td>2029.9389</td>\n",
       "      <td>6</td>\n",
       "      <td>1</td>\n",
       "      <td>新客户</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1510 rows × 5 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "            OrderDate          M   F    R   label\n",
       "CustomerID                                       \n",
       "AA-10315   2014-12-23  3889.2065  17    8  重要价值客户\n",
       "AA-10375   2014-12-25  1904.5380  14    6    潜力客户\n",
       "AA-10480   2014-08-28  7752.9070  10  125  重要挽留客户\n",
       "AA-10645   2014-12-03  3539.8788  19   28  重要价值客户\n",
       "AA-315     2014-12-29   787.3920   3    2     新客户\n",
       "...               ...        ...  ..  ...     ...\n",
       "YS-21880   2014-12-22  7282.4740  19    9  重要价值客户\n",
       "ZC-11910   2014-06-14     7.1730   1  200    流失客户\n",
       "ZC-21910   2014-12-28  4922.8390  27    3  重要价值客户\n",
       "ZD-11925   2014-12-28   856.2600   8    3     新客户\n",
       "ZD-21925   2014-12-30  2029.9389   6    1     新客户\n",
       "\n",
       "[1510 rows x 5 columns]"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# data['OR']=data.OrderDate.dt.year\n",
    "# data\n",
    "# data.rename(columns={'Order-year':'juck','OR':'Order-year'},inplace=True)\n",
    "# data\n",
    "# 读取2014年的客户信息\n",
    "data_14=data[data['Order_year']==2014]\n",
    "data_14\n",
    "# # 2.获取相应的列 \n",
    "data_14 = data_14[['CustomerID','OrderDate','Sales']]\n",
    "data_14 \n",
    "# 3.复制数据\n",
    "customerdf=data_14.copy()\n",
    "customerdf\n",
    "# 4.设置CustomerID为索引 \n",
    "customerdf.set_index('CustomerID',drop=True,inplace=True)\n",
    "# 添加交易次数字段\n",
    "customerdf['orders']=1\n",
    "customerdf\n",
    "# 6.透视 \n",
    "# 最后一次购买时间  购买次数   购买总金额 \n",
    "rfmdf=customerdf.pivot_table(\n",
    "    index=['CustomerID'],\n",
    "    values=['OrderDate','orders','Sales'],\n",
    "    aggfunc={\n",
    "        'OrderDate':'max',\n",
    "        'orders':'sum',\n",
    "        'Sales':'sum'\n",
    "    }\n",
    ")\n",
    "rfmdf\n",
    "# 7. 每一位用户的 R F M \n",
    "# 用相同的的标准减去每一位用户最后购买的时间即可算出R,标准一样,则R标准一样\n",
    "rfmdf['R']=(rfmdf.OrderDate.max()-rfmdf.OrderDate).dt.days\n",
    "rfmdf.rename(columns={'Sales':'M','orders':'F'},inplace=True)\n",
    "rfmdf\n",
    "# 8.3用户打标签算法  \n",
    "def rfm_func(x):\n",
    "#     与均值的差设置成0和1状态\n",
    "    res=x.apply(lambda x:'1'if x>0 else '0')\n",
    "    label=res.R+res.F+res.M\n",
    "    d={\n",
    "        '011':'重要价值客户', \n",
    "        '111':'重要唤回客户',\n",
    "        '001':'重要深耕客户',\n",
    "        '101':'重要挽留客户',\n",
    "        '010':'潜力客户',\n",
    "        '110':'一般维持客户',\n",
    "        '000':'新客户',\n",
    "        '100':'流失客户'\n",
    "    }\n",
    "    result=d[label]\n",
    "    return result\n",
    "\n",
    "\n",
    "# 8.用户打标签 \n",
    "# 8.1 用户的R值F值M值与均值比较 \n",
    "# rfmdf[['R','F','M']].apply(lambda x: x-x.mean())\n",
    "# 8.2 用户R值差 F值差 M值差 划分 0或1 \n",
    "#  rfmdf[['R','F','M']].apply(lambda x: x-x.mean()).apply(rfm_func,axis=1)\n",
    "# 将RFM进行连接,每个RFM之分别于均值做差,然后用函数将每个用户打上标签\n",
    "rfmdf['label']=rfmdf[['R','F','M']].apply(lambda x:x-x.mean()).apply(rfm_func,axis=1)\n",
    "rfmdf"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "17ba7710",
   "metadata": {
    "hidden": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:>"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1224x504 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 计算每种客户类型的数量\n",
    "rfmdf.groupby('label').count()\n",
    "# 将每种客户类型作为横坐标,客户类型的值即数量作为纵坐标进行绘图\n",
    "rfmdf.label.value_counts().plot.bar(figsize=(17,7),fontsize=18)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "c5fae36f",
   "metadata": {
    "hidden": true
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "id": "5e7c5a61",
   "metadata": {
    "heading_collapsed": true
   },
   "source": [
    "# RFM的评分算法(拓展)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 75,
   "id": "f4382143",
   "metadata": {
    "hidden": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>R</th>\n",
       "      <th>F</th>\n",
       "      <th>M</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>1510.000000</td>\n",
       "      <td>1510.000000</td>\n",
       "      <td>1510.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>61.747020</td>\n",
       "      <td>11.572848</td>\n",
       "      <td>2838.095210</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>74.135957</td>\n",
       "      <td>8.435837</td>\n",
       "      <td>2891.957839</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>2.052000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>13.000000</td>\n",
       "      <td>4.000000</td>\n",
       "      <td>531.277500</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>33.000000</td>\n",
       "      <td>10.000000</td>\n",
       "      <td>1920.083460</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>82.750000</td>\n",
       "      <td>17.000000</td>\n",
       "      <td>4372.589475</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>362.000000</td>\n",
       "      <td>48.000000</td>\n",
       "      <td>23295.218400</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                 R            F             M\n",
       "count  1510.000000  1510.000000   1510.000000\n",
       "mean     61.747020    11.572848   2838.095210\n",
       "std      74.135957     8.435837   2891.957839\n",
       "min       0.000000     1.000000      2.052000\n",
       "25%      13.000000     4.000000    531.277500\n",
       "50%      33.000000    10.000000   1920.083460\n",
       "75%      82.750000    17.000000   4372.589475\n",
       "max     362.000000    48.000000  23295.218400"
      ]
     },
     "execution_count": 75,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "customer_grade_df = rfmdf[['R','F','M']]\n",
    "customer_grade_df.describe()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f6f68be0",
   "metadata": {
    "heading_collapsed": true
   },
   "source": [
    "# 打分区间"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 79,
   "id": "7b3aa9bb",
   "metadata": {
    "hidden": true
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\阚其禄\\AppData\\Local\\Temp/ipykernel_4628/2021258731.py:5: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  customer_grade_df['F_S']=grade_F.values\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
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       "\n",
       "    .dataframe tbody tr th {\n",
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       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>R</th>\n",
       "      <th>F</th>\n",
       "      <th>M</th>\n",
       "      <th>F_S</th>\n",
       "      <th>M_S</th>\n",
       "      <th>R_S</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CustomerID</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>AA-10315</th>\n",
       "      <td>8</td>\n",
       "      <td>17</td>\n",
       "      <td>3889.2065</td>\n",
       "      <td>4</td>\n",
       "      <td>3</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>AA-10375</th>\n",
       "      <td>6</td>\n",
       "      <td>14</td>\n",
       "      <td>1904.5380</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>AA-10480</th>\n",
       "      <td>125</td>\n",
       "      <td>10</td>\n",
       "      <td>7752.9070</td>\n",
       "      <td>2</td>\n",
       "      <td>4</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>AA-10645</th>\n",
       "      <td>28</td>\n",
       "      <td>19</td>\n",
       "      <td>3539.8788</td>\n",
       "      <td>4</td>\n",
       "      <td>3</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>AA-315</th>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>787.3920</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>YS-21880</th>\n",
       "      <td>9</td>\n",
       "      <td>19</td>\n",
       "      <td>7282.4740</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ZC-11910</th>\n",
       "      <td>200</td>\n",
       "      <td>1</td>\n",
       "      <td>7.1730</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ZC-21910</th>\n",
       "      <td>3</td>\n",
       "      <td>27</td>\n",
       "      <td>4922.8390</td>\n",
       "      <td>5</td>\n",
       "      <td>3</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ZD-11925</th>\n",
       "      <td>3</td>\n",
       "      <td>8</td>\n",
       "      <td>856.2600</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ZD-21925</th>\n",
       "      <td>1</td>\n",
       "      <td>6</td>\n",
       "      <td>2029.9389</td>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1510 rows × 6 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "              R   F          M F_S M_S R_S\n",
       "CustomerID                                \n",
       "AA-10315      8  17  3889.2065   4   3   5\n",
       "AA-10375      6  14  1904.5380   3   3   5\n",
       "AA-10480    125  10  7752.9070   2   4   3\n",
       "AA-10645     28  19  3539.8788   4   3   5\n",
       "AA-315        2   3   787.3920   1   2   5\n",
       "...         ...  ..        ...  ..  ..  ..\n",
       "YS-21880      9  19  7282.4740   4   4   5\n",
       "ZC-11910    200   1     7.1730   1   1   2\n",
       "ZC-21910      3  27  4922.8390   5   3   5\n",
       "ZD-11925      3   8   856.2600   2   2   5\n",
       "ZD-21925      1   6  2029.9389   2   3   5\n",
       "\n",
       "[1510 rows x 6 columns]"
      ]
     },
     "execution_count": 79,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 1.1 F值区间打分 F值越大,分越高\n",
    "section_list_F=[0,5,10,15,20,50]\n",
    "grade_F=pd.cut(customer_grade_df['F'],bins=section_list_F,labels=[1,2,3,4,5])\n",
    "grade_F\n",
    "customer_grade_df['F_S']=grade_F.values\n",
    "# 1.2 M值区间打分 M值越大,分越高\n",
    "section_list_M=[0,500,1000,5000,10000,30000]\n",
    "grade_M=pd.cut(customer_grade_df['M'],bins=section_list_M,labels=[1,2,3,4,5])\n",
    "grade_M\n",
    "customer_grade_df['M_S']=grade_M.values\n",
    "# 1.3 R值区间打分  R值越小,分越高\n",
    "section_list_R=[-1,32,93,186,270,365]\n",
    "grade_R=pd.cut(customer_grade_df['R'],bins=section_list_R,labels=[5,4,3,2,1])\n",
    "grade_R\n",
    "customer_grade_df['R_S']=grade_R.values\n",
    "customer_grade_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 85,
   "id": "9bdb74d2",
   "metadata": {
    "hidden": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Index: 1510 entries, AA-10315 to ZD-21925\n",
      "Data columns (total 6 columns):\n",
      " #   Column  Non-Null Count  Dtype   \n",
      "---  ------  --------------  -----   \n",
      " 0   R       1510 non-null   int64   \n",
      " 1   F       1510 non-null   int64   \n",
      " 2   M       1510 non-null   float64 \n",
      " 3   F_S     1510 non-null   category\n",
      " 4   M_S     1510 non-null   category\n",
      " 5   R_S     1510 non-null   category\n",
      "dtypes: category(3), float64(1), int64(2)\n",
      "memory usage: 84.5+ KB\n"
     ]
    }
   ],
   "source": [
    "customer_grade_df.describe()\n",
    "# 可以查到R_S,F_S,M_S 不是浮点型数字,是个category类型 无法进行计算,需要进行转换\n",
    "customer_grade_df.info()   "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 87,
   "id": "c3ca633e",
   "metadata": {
    "hidden": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "R_S    int64\n",
       "F_S    int64\n",
       "M_S    int64\n",
       "dtype: object"
      ]
     },
     "execution_count": 87,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "rfm_score_grade=pd.DataFrame(customer_grade_df[['R_S','F_S','M_S']],dtype=np.int64)\n",
    "rfm_score_grade.dtypes"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6deeb713",
   "metadata": {
    "heading_collapsed": true
   },
   "source": [
    "# 根据打分情况,给用户打标签"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 91,
   "id": "c1433d4e",
   "metadata": {
    "hidden": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>R_S</th>\n",
       "      <th>F_S</th>\n",
       "      <th>M_S</th>\n",
       "      <th>RFM</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CustomerID</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>AA-10315</th>\n",
       "      <td>5</td>\n",
       "      <td>4</td>\n",
       "      <td>3</td>\n",
       "      <td>重要唤回客户</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>AA-10375</th>\n",
       "      <td>5</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>重要唤回客户</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>AA-10480</th>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>4</td>\n",
       "      <td>重要深耕客户</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>AA-10645</th>\n",
       "      <td>5</td>\n",
       "      <td>4</td>\n",
       "      <td>3</td>\n",
       "      <td>重要唤回客户</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>AA-315</th>\n",
       "      <td>5</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>流失客户</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
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       "      <th>YS-21880</th>\n",
       "      <td>5</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>重要唤回客户</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ZC-11910</th>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>新客户</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ZC-21910</th>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>3</td>\n",
       "      <td>重要唤回客户</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ZD-11925</th>\n",
       "      <td>5</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>流失客户</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ZD-21925</th>\n",
       "      <td>5</td>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>重要挽留客户</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1510 rows × 4 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "            R_S  F_S  M_S     RFM\n",
       "CustomerID                       \n",
       "AA-10315      5    4    3  重要唤回客户\n",
       "AA-10375      5    3    3  重要唤回客户\n",
       "AA-10480      3    2    4  重要深耕客户\n",
       "AA-10645      5    4    3  重要唤回客户\n",
       "AA-315        5    1    2    流失客户\n",
       "...         ...  ...  ...     ...\n",
       "YS-21880      5    4    4  重要唤回客户\n",
       "ZC-11910      2    1    1     新客户\n",
       "ZC-21910      5    5    3  重要唤回客户\n",
       "ZD-11925      5    2    2    流失客户\n",
       "ZD-21925      5    2    3  重要挽留客户\n",
       "\n",
       "[1510 rows x 4 columns]"
      ]
     },
     "execution_count": 91,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "def rfm_score_func(x):\n",
    "    level=x.apply(lambda x: '1'if x>=0 else '0')\n",
    "    label = level.R_S+level.F_S+level.M_S\n",
    "    d={\n",
    "        '011':'重要价值客户', \n",
    "        '111':'重要唤回客户',\n",
    "        '001':'重要深耕客户',\n",
    "        '101':'重要挽留客户',\n",
    "        '010':'潜力客户',\n",
    "        '110':'一般维持客户',\n",
    "        '000':'新客户',\n",
    "        '100':'流失客户'\n",
    "    }\n",
    "    result=d[label]\n",
    "    return result\n",
    "rfm_score_grade['RFM']=rfm_score_grade[['R_S','F_S','M_S']].apply(lambda x:x-x.mean()).apply(rfm_score_func,axis=1 )\n",
    "rfm_score_grade"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 110,
   "id": "10b3ec0e",
   "metadata": {
    "hidden": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:>"
      ]
     },
     "execution_count": 110,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
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4LOQkSZIkqWMs5CRJkiSpYyzkJEmSJKljLOQkSZIkqWMs5CRJkiSpYyzkJEmSJKljLOQkSZIkqWMs5CRJkiSpYyzkJEmSJKljLOQkSZIkqWMs5CRJkiSpYyzkJEmSJKljLOQkSZIkqWMs5CRJkiSpYyzkJEmSJKljLOQkSZIkqWMs5CRJkiSpYyzkJEmSJKljLOQkSZIkqWMs5CRJkiSpYyzkJEmSJKljLOQkSZIkqWMs5CRJkiSpYyzkJEmSJKljLOQkSZIkqWMs5CRJkiSpYyzkJEmSJKljLOQkSZIkqWMs5CRJkiSpYyzkJEmSJKljLOQkSZIkqWMs5CRJkiSpYyzkJEmSJKljLOQkSZIkqWMs5CRJkiSpYyzkJEmSJKljLOQkSZIkqWMs5CRJkiSpYyzkJEmSJKljLOQkSZIkqWMs5CRJkiSpY4ZSyEXEnIj4aETcFBG/iognDePvlSRJkqTpaNaQ/p4zgGcDxwPbAOdFxH6Z+csh/f2SJEmaphacfGHTIUy5Jacf0XQIarmBF3IRcX/gGODozDy7HtsPOBE4btB/vyRJkiRNN8PokTsUWAV8oe/Yl4H3DuHvliRJktSw6dZr2oYe02HMkdsRWJyZy/uOXQPsGhEzh/D3S5IkSdK0MoxCbi5w85hjy4GZwLZD+PslSZIkaVqJzBzsXxDxeuDpmfnovmN/Afwa2Dkzr+07fhxr583tCUy3xVB2AG5oOghtkPlpP3PUfuao3cxP+5mjdjM/7TfdcrRrZs5fX8Mw5shdTxle2W+7+nxH/8HMPBM4cwgxNSIiFmbm/k3HofUzP+1njtrPHLWb+Wk/c9Ru5qf9RilHwxha+TNgl4joL+b2Be4Elg3h75ckSZKkaWUYhdwi4FrgBICImAUcC1ycgx7XKUmSJEnT0MCHVmbm6oh4HXBOROwB3A/YDzh40H93C03bYaPThPlpP3PUfuao3cxP+5mjdjM/7TcyORr4Yidr/qKIJwNvABI4LTP/eyh/sSRJkiRNM0Mr5CRJkiRJU2MYc+QkSZIkSVPIQk6SJEmSOsZCTpIkSZI6Zhgbgo+kiJgLHAbcBayiLPIyA9gMuCwz3UOvQean/cxRu5mf9jNH7WeO2s38tJv5cbGTgYmIXYHfUf6ninq49499WGZe2khgAsxPF5ijdjM/7WeO2s8ctZv5aTfzY4/cMDygPgewGHgY8PPmwtEY5qf9zFG7mZ/2M0ftZ47azfy028jmx0JusDIzr+q9iQiAWzNzVXMhqY/5aT9z1G7mp/3MUfuZo3YzP+020vlxsRNJkiRJ6hh75AYgIvYGtm46Dq2f+Wk/c9Ru5qf9zFH7maN2Mz/tZn4Ke+SmUERsERFfBxYBz2g4HI1hftrPHLWb+Wk/c9R+5qjdzE+7mZ91WchNocy8HfgxcBDwoYbD0Rjmp/3MUbuZn/YzR+1njtrN/LSb+VmX2w8MSF0SdXFmzuw7thpYkJlXNxeZwPx0gTlqN/PTfuao/cxRu5mfdjM/9shJkiRJUue42MmARcTBrLtJ4YERsTIz/9hgWKrMT/uZo3YzP+1njtrPHLWb+Wm3Uc6PQysHpNfdC6wAVgKrgM2B2ZT/yX4PnAt8qH//Cw2H+Wk/c9Ru5qf9zFH7maN2Mz/tZn4s5IYuIrYEdgUOB14M7A18AjglM29pMDRhfrrAHLWb+Wk/c9R+5qjdzE+7jVJ+LOQaFhHHAGcAT8vMbzYdj9ZlftrPHLWb+Wk/c9R+5qjdzE+7Tef8WMi1QETsmZm/bDoOrZ/5aT9z1G7mp/3MUfuZo3YzP+02XfNjITdkETEX2CEzr206Ft2T+Wk/c9Ru5qf9zFH7maN2Mz/tNkr5cfuBAYiI70XEJXXn+bEeACyJiOcMOy4V5qf9zFG7mZ/2M0ftZ47azfy0m/kpLOQG40BgEfDf62m7H+Xf/UfDDEjrMD/tZ47azfy0nzlqP3PUbuan3cwP7iM3SO/PzKsj4lGZ+b2+4w8GlgLfjIhllOVRZwNbZ+auTQQ6osxP+5mjdjM/7WeO2s8ctZv5abeRz489coN3aUS8se/9AcC3gJ2BD1BW0XkAcOrQIxOYny4wR+1mftrPHLWfOWo389NuI5sfFzsZgIhYDSyodwlWAzcAnwFOAv5Yn/8tM2fW82/KzO0bC3jEmJ/2M0ftZn7azxy1nzlqN/PTbuansEdu8BI4GHgucD4wrz5Hk0FpDfPTfuao3cxP+5mj9jNH7WZ+2m1k82MhN4Ui4kkRcS3lf6g16r4VzwGeCnw2M29rIr5RZ37azxy1m/lpP3PUfuao3cxPu5mfdVnITa07gUvr61kRsVNf24HAamCXoUelHvPTfuao3cxP+5mj9jNH7WZ+2s389MtMH1P8oPxP9AbgKmAVZfWcW4BnAcuBvYBVfeff1HTMo/QwP+1/mKN2P8xP+x/mqP0Pc9Tuh/lp98P8lIc9coOzBLieMj73IuC0zPxP4IvA0QARsXdEPAyYWV9P+7G8LbIE89N2SzBHbbYE89N2SzBHbbcEc9RmSzA/bbaEEc+PhdzgfA84CPggpYv3F/X4F4AjKf/T/ZSymeFWfc8aDvPTfuao3cxP+5mj9jNH7WZ+2m3k8+OG4IOTmbkKOCEiVgGfi4hDKON69wQeDVxZz50JzM3MW5sJdSSZn/YzR+1mftrPHLWfOWo389NuI58fC7nBeW9E3JaZLwVeB6wELs/MFRHxR+DRue4u9Bou89N+5qjdzE/7maP2M0ftZn7abeTz44bgAxARX6dMtJyTmU/cQPvdmfnkoQcn89MB5qjdzE/7maP2M0ftZn7azfwUFnINiIi9gStrd7CGLCK2z8yb6usHADtl5rf72s1Py5mjdjM/7WeO2s8ctZv5abdRyY+FnEZKRLwH2DYzj63vXwAcXrvl1UERsRmwZ2Ze3nQsUttExBxgZWau7ju29XSbJyINWkTMAB6TmZd6DaktnCM3AHVzwpXA3fWxITOB2cCszPzDMGITs4Ad+t7fDfxNRDx2Iz8zm9J1f+8BxqU+ETELOBM4LjM3dg0B3Av4PrDFwAPTRkXEzsD7M/Nv+o5tC3wdODYzf9pUbCPsg8CngB8ARMQ8YFlEzMvMFY1GNuIi4j+BXwOLgd8B383M5c1GpX4RMRfYvn5HmwlcEhGbU66hbTLztmYjVERsD7wIuKk+llH2k1sGLM3MuxoMb+As5AbjGmBCXZ0RsZ13d4biUuDAMce+D3xkIz+zGTBnYBFpfVZRPpiPjYhnAFtTNv9cny0pN040ZBFxX+CkzDypHpoLPGnMaU8BHgFsM8zYRllE3Bu4s/cWmB0RW9f3M+qxufVLau+ceZn5p+FGOvKeSbnJ8QTKCnu/AA6IiB9Q8jd2SNgsyqp7jxxqlKPtr4APA7tm5sqIIDPvioiwiGuN+cB7xxxb8x08Im4BLgf+KTO/OszAhsFCbnD2ATZVmAXlTtxuwP8NOiABZRnaHcccW5KZFzQRjNYvM7P+wlwVEW8A7qAsI/wd4FGUvWN672ex4SJPg7U18AqgV8itAMbe/Xwt8P3MvHSYgY24P1G+yER9PnZMe1LuVvf0zps5lOi0Rm+Rhoh4JnBuRNwPOAB4GyUvbwbeDrylHtNw3UlZUKMnImIxkPW53zLg9LohtYbrZuC+lD3itqL8btqWUuQtAI4BPh8R983MafV92zlyA1D3shhXD1tErMpMf3kOSURsSel6/0w9tBvl4r+YUizcQfkS9BtgYWYuW9+fo8HrXRsRcWlmHhIRyzJzu4j4Y2ber+/9tsDizNy+6ZhHTUTsCizKzO363v+kl4uI+Bvgs8AjM/PHzUU6WiLiPpQvoAG8C/g05Y409diNwPasLeBmUHrkHOI/RBGxGpifmTdGxMOAw4FPALdm5ox6Tu9zcHXvmIYnIg4HPpSZD67vVwNHAefX535/RZlzv9dwoxxtEbEn8L2NfQeIiEOBS4AnT7deOXvkBiPWvChDJJZTegyCMkTv8Zl5R0OxjbTMvC0i/pWSj1XAIkpeAticcvfmUcBDgftExI+AzwGftKgbjoiYTfkyQ0S8mHJXDdYOlRh798m7Uc1a779/Leo+DLzLIm7ong3cQLkxtSOwH+UudW/uNsAWYwo3P9+acX1EXAG8NTPfDxARfqY1LCLuonx3mwHMi4ibqDc+MvOCOmLkgjE/83vg4OFHq3FYUp/3BCzkNCEHACfU10EZx+u/e7PeRLkr8+m6otvHgNdTJseeArw2M2+qS9c+hTI07CWU4k6DtxVlaDLAPwPzmgtFf46IOITS631xZv5D0/GMoOMpN6tWUAq5PShDXmdQbiYGcHVE3Ap8A/hw/xYsGryImEm5CfJwSs/OZyLinzPzLfTdDFZjjqL0au8L/D1lznYA/z32xDrX9ADKEPKHDzNIjdutlJx+pelAppoFxeBlZn6w9yYi3tdkMAJgF+BfIuIblGGWL6LMQ4AyD+FTEfEY4AzgH4HdgQc2Eegoqnv87VOHFO0QEX7BbJGIOAL4W0qPzzzKohn/BNxOKRK2pfyyfBPwgWaiHG2ZuWfvdUR8jDKi4LL6fgalZ24rYC9K791FEfEF4KXTfc+lFplLKQz+mJmnRcQlwDcjYiFARKzpxa6v7aUbosy8CNYU3Msz83/q+zXn1LZXUL4/bEMp+q4cerAjKCIeQrkxdTuwUzkUW2Tm7es7v46ompZrIVjIaRStoHyR+X/1NawdchSU5ew/VB9nZeadrJ1fouGbXb9kblmft6vPW9Tn2c2GN3JmU3p7tqYMR54BPIC1E8upx7ahrPg6rZd+7oAfsu6wyTnA1ZSh5Tdl5skR8f+Af7SIG57MvL0uX99beOFm4OWsHfb1Qcrvo3+trz859CAFpeBeZ9XqejMEyk3hk4ELKYuc/HLIsY2yDwOHsu4Njlsj4mbgCuDbwGcz84oGYhsqFzsZgDoZdtvMvLW+PpS1QyUuoW8hFBc7Ga6IOA54fH3sSVnN7TTKHbXbKD0Ip1LGxveWtL8ZOH+6rXTUZvVO50rKzaZXUvb+29DKlHOBv8vMbYcTnXoiYgHw477FTRZQ5p2+AHgP5dp5Su1l1RDVYeMXZubjI+JNwLspC5xcRFn2/lDKtiuHZeYPm4t0NEXEuyiF9Lsi4lTKsP6HZObi/oVNXOykWXXbjj0pwyx/DfycMs3iM8DzgZXj2OtUUywi9qXcMLybsmjdWcALKcX1PpSFZ3YCvgwcn5nXNBPp4FnIDcCYQm4pZcJ5b7GTucDuvaLAQm64IuIrlJ6Evfq+fK4GvkspHA6lLG1/F2sXQdkX+HJmvqCRoEdQRBwG7E2Zu7PRrQXqXma/y0zn0g1RlDFGu7DuKpVrVq2MiC2A/6IUD49y8+nhqr0G/5eZW0TEbZQ8bAv8EXgkZfjrSZl5VnNRjq666NYcynCv04E7MnPv2mYh1yIR8XDgB5k5t37u/XtmHt10XCo2tGplRDydMs/+XpQbit9tIr5Bc2jlgGXm/E2fpWHJzCdFxIOA70bEXwNPp3TNPxO4nnJ354XAq4C3ZeayiPgX4C+ainnU1KXTv1EfP4yITS2Jvg1w4sAD0xoRsRvwJeDfNnROHTp2FPBT4P2UnlUNWJTNwD9N6UGYVYcfb0bZBmIzys2pd1KGix8ZEUfWH52TmUcMP+KRdRFlHumLgEuBMyPiqMw8H+fDNS4iXka5Vnorv66OiBfWY3tFxPoKuRuAr27q5qMG4h4LBNXVRS8BvgB8LSIOzsxFQ49swCzkBiPxg7jNZlHuhO4CfAvofWDPqM8PB54BHBURLwBOy8zfNxPq6MnM6+rePa+k9JT2rqWNreSWwEcHHZvWWAV8nnLtbBkRx1NWf11H3e7jZcBXI+LMzPzpkOMcRXdSPtfupKy6+z/AE4HLKNfQk4FdKcPFvgOcx9rtVzQ8VwC71HmJ10XEJ4B3UPYni1qA0/+695yZz2gi4BHzXMqQ/rsp3xdmU1awhtKz/V7g2jE/sytl7v3rhxOiqpmU72/3UEfGPZUyZ+78iNgnM28ZanQD5tDKAahD9cb7DxuUeSS7OgdrOCJiL+DTmbl/RGxOmRu3G6VH7krgkPr67cBrKPv+uXJiAyLiYOBMypDkY4CF6zltNqU3wWK7ARHxXKC3auWLgW9l5pZjzrkEuD0znzL8CEdTRMyiDBGfTdlaZQ9KAf4n4BHAfSkLaXwNeJlDX4crIran9OAsqYdmADsDLwUeTSnE+xefCepNyMw8dniRqn5n+GFmblXf70sZErtHXQytd94zKSN53KpoiCJiH8rQ1zkbOWd3yuiQT2bm8cOKbRjskRuMQyi/QFex7gfxWLMov2RnUb4EaQgy8+fA/vXtcsocuD9k5kpKQdfzhog4NzN/NOwYVWTmtyPiEcC/UyaX75WZNzcblfpl5mcj4kLKMty3UAqFsT4BbLme4xqcGZQtVAL4S0rRMB+4CiAzvxIRB1H2xXoP8OqG4hxJda/Sv6N8V0jKzapHA1dk5r83GpzG2oySn55FlCH9J1F6UXuuwOuoCddQFq7boMz8dUS8gzICYVqxR05S69UJ5gsy83dNx6Lxq6uPPg+4wBEH7VTnO95c91mSNEZEzAZ2zMyr+o49itIL5Hy4lomInafzKpVjuQLSkEXE7Ih4Rd/7bZqMR+qIzYBbmw5CRUTMj4jLxhzbqS600e+RlN4ehya3VL054v5xLRbF45qOY1Rl5sr+Iq4e+15/ERcRuww/stEWEZtFxGkRMa/3+ygijqWsljwy7JEbsDoudwVr58zNBBZl5ja1/RNAZuZxDYUotV5EvJ4yd+TB3gFtXp3fsyQzt67v96aswveuzPzwmHPvTRm67FD+IYqIz1LmWf2pbvo9jzLM8v+ALXpze2qv6ULgAw7pa1ZdGKg352pOZp5Zjx9EWZjmwsx8WlPxjaKI2Ap4TWaeVt9v3bcP8M6ZeU2da39zZm7WZKyjJiI2o8wx3QX4LfD3lJWUnwU8lTJt6W7W7kE7k3JdvXzYsQ6ShdwARMRuvSFgEbGMsm9Z/4p7N9d9lrYBrqZ8SHyqgVCl1qtDv34CvLf3y1TNqp9dv6ufYwdS9iS7Eng5ZSjlXX2n3x84OjPn3vNP0qDURbc+CPyeMj9xb+A5lBuLszJzdR2y/GngKOCgzLy8qXhHVURs1ltopubsW5TvC4f07zFbF9xYtLEFHTT1ImIH4JrMnFf3LF1S95ObQ/kuN68Ovbw5M7doNtrRUG8+fYuyJ+YTKZ9hxwJLgadn5sL63fvfKFtJnVF/9OXAxzLztWP/zC7zDulg/CIiPgm8D2Dsht8RcVN9+QnK5rkWcdJ6RMSWwH8ClwDfiYizWbeHu2cWMDcznz3kEEda3XT6bODjwKGUBQF2Y91CLikLoWi4MjNPqCvpnU0p1lbV46sj4v7Ap4ADgCdbxDXm1xHxZsqXUTLzcbCmqFsjM38eEQ6BHaLa47MZaz/P7qL8/qE+r4Qy9DIi7rrnn6ABCcq+mCuAwyirUa6gfL69oi4i1Pv8e3VmngAQES+ebkUcWMgNymzgQcAvWP82BHMj4geU//HcgFVaj3r380uUoRMvoCyZfgvrL+Rms27xoMF6LEAtCB5F+bd/ZmYuBJ7fZGC6h3cBr8zMr8Ca+VYfp1xT3wD2ycwlDcY36nambNB+ImM+1+oN4Z77UlZZ1hDUGyAfoNxwn1dzsRmwWV9eeq83tsepplhm3g18pN7ofSdlVeu3UfbGPBu4kDKM8h4/OrQgh8hCborVO9SZmYfVvS2+ExFXUj6AV1K+8Myh9MRNq3G60lSo8w3eBxwJfAR4R5Yx4N+tDzUoIj4DPBNYHhEPzMzf1qEu20fEU4D/oMxL6JlB6S11aGUznghcXe9S9+Zf/TVl2OUvgUMi4hDK94HtMvO9zYQ5shJ4IGVo2Ifq94VFfW1X19dLgNOHHdwIWwa8hbJwximUbTvmUnLSW/ik99pCrgGZeVtE/AVlDtxbM3N5RLycMoRyv2ajGx7nyE2hiHg85X+go3rDKes43edSCrgZwDzKPhY/p8xdeG5muoecVNXV2b5A+dL5/My8uOGQ1CciXkgZyvIDys2pd2XmOyPiTmAB8BDWX8h9ZdixjrKIWJWZM2uRvTnwY8o19RDgRsreS/1fQHt52nPowY6giHgNcCZwW2bOqMdWU25gHQD8AyVflwDHu/XKcPUWNRkzH3hbYHFmbl/PWZaZ29XXN/WOa3giYlFm7hMRiyk3GC8CDqJ0lmwfEav7rq9pmSN75KbeQ6HsMZKZ36P0zn2t/4SIWE75oP4P4FwcXimtkZkXR8SOwAnAeRHxKcod0T0pc61+D1wHXA/8b2b+prFgR1Bmfrp+ubkTeALwrxHxAEpRtyclb38AFgP/H3BpesewSZ8F3pOZu8OaYmE74JuUu9i/bDK4UVSHjb8ReB3rDvfKzPwi8MWIeCPlenoX8JOIeHpm/s/wox1Zp0fEAcA5wIyI2BnYtu91UEYq916vOZ6ZV2/oD9XUiIhzgZuBXSPinZTPtC8Br87Mq8o6TqPBfeSmUGZ+k3K38zTgmxHxDMqFfnH/o567CngxsHdEPLmxoKUWysw7MvOdwMMod9cuBLaiDEveHXgS8AbgpxGxMCIe3Viwo2kzyhL2lwEHAjtQen12AP6XssT9I4AvAlfUFffUjG8AF8Tafa6SkpsVlALh1DolQEOSmX8CdqWspndHRHyuLnMfNR9vqeddk5nPBz4GfD4iFjQW9Og5j7Iy4isoK48voQx53ZoynHLJBl7bczpg9fNqEWVo+CrK75s5lEL7MRExq5wWi+v5i+vrberrHRsJfEAcWjkgEXEMZZ7POyk9B70VqGYA7+vrjn8LZZnhwxsJVGq5KPtffZ2y1PBz+nt3ImI7yjyGVwAvz8xPrv9P0VSKiPsA3wf2zMwVdfntDwKnZuYNfedtCXyYMifrEZn5h0YCHkG15+1FlN6CfSirih5EGeY/OzNXRcRjgc8AvwGelZlLGwl2hEXErpRen2uAWyn5uZsyzPXlfed9DSAz/7qJOEdZRDwGeA1wOPAvwGmZeUdf+86UOXXLKXlzusyQRMTvMnO3iPgd8DjKSLergQvqKSvrIyjfv+cA52fmtFk4yEJuACLiIZS7nQ8HfjimeS7lTs9jM/OmiNiXstrbm4YcptRKEbE1sEddAbF3bAfgMsqc0h+s52dOouyD9TfDi3R01eL6tcDpdXQBEbFDZt4QEccB12bmRX3nfwk4JTOvaCbi0VNXRl5O+eJyKPASyr5Kn6XcEOntXbYTZR/AAB6emavX+wdqYCLiYcBhmfnBKPtmPiwzLxhzzu6UXoj9HA47XFG2h/gRpVg7LjNfUoeT/2VmfiYi/hW4PDM/0GScoygi5mfm0oh4T2a+LiK2p3zGPaX3GTfdWcgNQL0Tmmx4JaMETsjMMzbQLo2siHgRZX+riynLP/+sNm1FGUKxPjOBbTJz0aDjE0TExyj7ku2fmddGxLMow8T2ooxEeC5lQZS3u8hJMyLiIOBpmfnG9bQ9jnK9nF/f70i5EfKFIYcpICJeChyZmU+LiHsBVwIHZ+avxpy3V2b+vJEgR0wd7XFHZt4VEadSVhW9HHhDZl4eEQ8ELqsLaryaUtQ9p8mYR039vfM+4CF1YZoDgAcDZ1FWgj2PsjXBWZl5Y3ORDpaF3AD0r5KzgfY1Kx1JWlddZe8xwPOAv6Ws9LqmeSM/mr3VYjU4EfEg4ArgcZl5af3CcyXwycz8h3rOvSkL1Pwd5cvPyZn5303FPGrqYho/AT6emW+NiC2AzwEvyswbI+KfgJdSFqz5NHC2BcJwRcQPKT2mqyh7xN2LMr8UypfR21m7zD2UG8Bfycx/Hmaco6quKnoc8HbKonRB6RGdD3wV+EdKvrYADqEUC9Nq7lWbRcT9Kb+HPpaZp9R5cZcDn6ufeTMoW6+8gjLk8iLKDeKv9kaRTBcWcgNQe+QOZcNfOr9MWanyurF33CStVZd7/gfgeMrCGa/NzN+POScow8dmZ+aGeuw0hSJin17vZ0QcSVlZ76GZuXLMeXtSNtS9IN2fbGgi4h3AfTPzmPr+FEqPwVP7zplNWa77lcBfUr6Uvi0zP99AyCMnIl7J2kLu0cC+lPmkUL47nEGZd9pblXdH4FRKT+pIDBlrUh06+bfA8ymLO30QeFp93oNyo2pryk3H6yl52j8zf9JIwCOm3lB8C/Di2mv6JOCfgH3HrpJcpzu9nbK1x7sz85RhxztIFnIDEBG/pcyRu4v17yQ/k/LF878y8w3DjE3qoojYg9KjkJRFM/zgapGImJuZd26gbQYwIzPvXl+7pl5EzAXo5SQiLgOevKHFTCLiYEoxfkxmXjm0QAWsWRztqMw8ou/YR4D79Ob91l7u9wCvysxbmol0NEXE4ZSi4THAm7Psm/lwypzTV1P21FxOWcjupMYCHXERsc3Gro06pPzbY284dp2FnKROqF9Od87MXzcdi9QlEbFtZt7cdBxavzovbpvMXNx3bFdgKxcIao86J+vi9c23iohHAT+cbsP21H7uHTNEETEnIo6uc4AkTUDtXbjaa0iamP4izt9D7ZOZN44p4norjTpvsSXqHKzfb2jRjMz8HmUDd2moLOSmWETMjYgNzXubTZlsObvv/AMj4mVDCU7qAK8haXK8htrPHHXObODbEbFdHeq/jroly6UR8cLhh6ZRNqvpAKahFcB9ACLi65RVwZIyJ+7JlOGs/XNJnkW58/bxIccptZXXkDQ5XkPtZ45ari6gsRxYDexE2ah9d+D7EbGIsvDJWXXO9omUhWu+2Ey0GlX2yE2xuplqb4z04ymbSP4EOGQDG60+EzhzSOFJrec1JE2O11D7maNO+DLwScpeZG8H3ktZUfSSevz1wE/qCqSnAi91IRoNm4udDEBE3FQ3iVyzn1z/MWDHzPxTRDwYuAy4d2be3mjQUot4DUmT4zXUfuao3da3529EHEjZFPwZdd7cl4AnAO/IzLc0EadGm0MrB2NWRBwCa5Z1nsG6/9b/GxHHAguAr/nBLN2D15A0OV5D7WeO2i0iYnfgxsy8aUzD7sBbgUcC5wAvjYiPZ+Yfhh+mRpk9cgMQEauAq4Fdgavq4Z0zc1a9y3YkZf+RVcBrMvPsJuKU2sprSJocr6H2M0ftFhF3ASuBzSkriJ4I3Ap8gzLH8RzgbZl5XUScDjw2Mw9qKl6NJufIDcYtmbkbQGbuVl/fWjfGJTO/CDwNuBewrLkwpdbyGpImx2uo/cxRi2XmnMzcEtiCshn7OcAzgJ8BO2XmKzLzunr6m4CtXFlUw2YhNzwBnEdZlQrgfsD1wDsbi0jqFq8haXK8htrPHLVIROxJycHFwMuA/wBeBewQEbv0HpQVSN8K/KKpWDWanCM3GNtExGKA3jOwFXBdPXYwcBhl6dqjI+LgzPx2I5FK7eQ1JE2O11D7maP2+159DkpxHcDWlCGW9B3bHLgWNwXXkDlHbgAi4jbgBcD5wFGUi/zTmblVHfd+K2VvkucBjwO2zcxXNRWv1DZeQ9LkeA21nzlqr4iYl5nLI+J3mblbHe76WOAHwLWZuV1dtfIo4IfALcDvgSMz8xuNBa6RY4/cYKzIzAsigsy8ACAiVva1v4gy1voyyuaf724gRqnNvIakyfEaaj9z1F7nRcTmwNyImEeZFwel8M567ArKZuHHZ+bXIuJNwE+bCVejykJuwCLizZS7bHN7x+oH96Mz8/aI+A3woIiYsYFNQKWR5jUkTY7XUPuZo9Z5N2VrgT1rz9yzMnMRQC28l0fECzPzu70fyMz3NxSrRphDK6dYRMwEbq5DI74J3Em5YzM3M5/Qv/FnPf++wB+A3TPzt81ELbWH15A0OV5D7WeOuiEibqbMWxxrBfB/wDWUBU4uAb6YmdcPLzrJHrlBmFsfZObj+xvqeGoiYk5m3lUPrwA+Bdw4zCClFvMakibHa6j9zFE37EX5t7+7vg9qQU0Z7roAeARlGOwZEXFMZv5HA3FqRNkjN0QRMRt4I/CPmblyU+dLWpfXkDQ5XkPtZ47aKyK2Ax66vtVDI+JA4H8z87bhR6ZRZSEnSZIkbUJEfBx4UWbO3eTJ0hC4IfgARcSf6t2bjZ2zeURcN6yYpC7xGpImx2uo/cxRp9xVH1IrWMgNQETMqS/vouwBs6Hzvk4Zez1vGHFJXeE1JE2O11D7maNOWlUfUiu42MkUi4hnAwcCJ1Iu9tUR8QvWrkg1A5iTmXsBj8jMuyPCDwWp8hqSJsdrqP3MkaSpYI/c1Nsd2KXvfQB7AB8E9gHOq++hLF0raV1eQ9LkeA21nzmSNGkWclNvEXDvMccSOKs+f6LvuJt6Sve0CK8haTIW4TXUdoswR5ImyUJu6v2GdT+ccwPPktbPa0iaHK+h9jNHkibNQm7qXQPsHBGnAtsCb6rHT63PJwH02uuzH9jSWl5D0uR4DbWfOZI0aRZyUywz76gvD6OsMHVoff/Y+vzoMe2HDS04qQO8hqTJ8RpqP3MkaSq4IfgARMQSyiTlXwB7AXcAm1GWD94R+ENmzoyIxZn5gIhYlpkb3UNGGiVeQ9LkeA21nznqnoh4P2VD8O2bjkUCe+QG5UZgmzHHHPcujZ/XkDQ5XkPtZ44kTYqF3GDcDvTfrQng6Pr6OX3H3cdPWj+vIWlyvIbazxx1zwxgZtNBSD0WcoNxJ2s/nBNYTNn083LgOOC3tW1efY6hRie1n9eQNDleQ+1njrpndn1IreBdnsH4CnAVpVCekZl/sYHz/isiZlPGxEtay2tImhyvofYzR92zGeZBLeJiJwMUEdcBD8rMZRs5Z3PgZxv5AJdGlteQNDleQ+1njrojIrYHtsrMq5qORQILOUmSJEnqHOfISZIkSVLHWMhJkiRJUsdYyEmSJElSx1jISZIkSVLHWMhJkiRJUsf8/wPE1bl+DDZXAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 1080x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 计算每种每种类型客户的数量\n",
    "rfm_score_grade.groupby('RFM').count()\n",
    "# 绘图\n",
    "rfm_score_grade.RFM.value_counts().plot.bar(figsize=(15,5),fontsize=16)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "2802c937",
   "metadata": {
    "hidden": true
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "28ff1cc6",
   "metadata": {
    "hidden": true
   },
   "outputs": [],
   "source": []
  }
 ],
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  "celltoolbar": "原始单元格格式",
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   "pygments_lexer": "ipython3",
   "version": "3.9.2"
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  "toc": {
   "base_numbering": 1,
   "nav_menu": {},
   "number_sections": true,
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   "title_cell": "Table of Contents",
   "title_sidebar": "Contents",
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   "toc_position": {
    "height": "calc(100% - 180px)",
    "left": "10px",
    "top": "150px",
    "width": "218.55px"
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   "kernels_config": {
    "python": {
     "delete_cmd_postfix": "",
     "delete_cmd_prefix": "del ",
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     "delete_cmd_postfix": ") ",
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     "varRefreshCmd": "cat(var_dic_list()) "
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   "oldHeight": 122.4,
   "position": {
    "height": "31px",
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